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100 Great Computer Science Research Topics Ideas for 2023

Being a computer student in 2023 is not easy. Besides studying a constantly evolving subject, you have to come up with great computer science research topics at some point in your academic life. If you’re reading this article, you’re among many other students that have also come to this realization.

Interesting Computer Science Topics

Awesome research topics in computer science, hot topics in computer science, topics to publish a journal on computer science.

Controversial Topics in Computer Science

Fun AP Computer Science Topics

Exciting computer science ph.d. topics, remarkable computer science research topics for undergraduates, incredible final year computer science project topics, advanced computer science topics, unique seminars topics for computer science, exceptional computer science masters thesis topics, outstanding computer science presentation topics.

Key Computer Science Essay Topics

Main Project Topics for Computer Science

We Can Help You with Computer Science Topics

Whether you’re earnestly searching for a topic or stumbled onto this article by accident, there is no doubt that every student needs excellent computer science-related topics for their paper. A good topic will not only give your essay or research a good direction but will also make it easy to come up with supporting points. Your topic should show all your strengths as well.

Fortunately, this article is for every student that finds it hard to generate a suitable computer science topic. The following 100+ topics will help give you some inspiration when creating your topics. Let’s get into it.

One of the best ways of making your research paper interesting is by coming up with relevant topics in computer science . Here are some topics that will make your paper immersive:

Evolution of virtual reality
What is green cloud computing
Ways of creating a Hopefield neural network in C++
Developments in graphic systems in computers
The five principal fields in robotics
Developments and applications of nanotechnology
Differences between computer science and applied computing

Your next research topic in computer science shouldn’t be tough to find once you’ve read this section. If you’re looking for simple final year project topics in computer science, you can find some below.

Applications of the blockchain technology in the banking industry
Computational thinking and how it influences science
Ways of terminating phishing
Uses of artificial intelligence in cyber security
Define the concepts of a smart city
Applications of the Internet of Things
Discuss the applications of the face detection application

Whenever a topic is described as “hot,” it means that it is a trendy topic in computer science. If computer science project topics for your final years are what you’re looking for, have a look at some below:

Applications of the Metaverse in the world today
Discuss the challenges of machine learning
Advantages of artificial intelligence
Applications of nanotechnology in the paints industry
What is quantum computing?
Discuss the languages of parallel computing
What are the applications of computer-assisted studies?

Perhaps you’d like to write a paper that will get published in a journal. If you’re searching for the best project topics for computer science students that will stand out in a journal, check below:

Developments in human-computer interaction
Applications of computer science in medicine
Developments in artificial intelligence in image processing
Discuss cryptography and its applications
Discuss methods of ransomware prevention
Applications of Big Data in the banking industry
Challenges of cloud storage services in 2023

Controversial Topics in Computer Science

Some of the best computer science final year project topics are those that elicit debates or require you to take a stand. You can find such topics listed below for your inspiration:

Can robots be too intelligent?
Should the dark web be shut down?
Should your data be sold to corporations?
Will robots completely replace the human workforce one day?
How safe is the Metaverse for children?
Will artificial intelligence replace actors in Hollywood?
Are social media platforms safe anymore?

Are you a computer science student looking for AP topics? You’re in luck because the following final year project topics for computer science are suitable for you.

Standard browser core with CSS support
Applications of the Gaussian method in C++ development in integrating functions
Vital conditions of reducing risk through the Newton method
How to reinforce machine learning algorithms.
How do artificial neural networks function?
Discuss the advancements in computer languages in machine learning
Use of artificial intelligence in automated cars

When studying to get your doctorate in computer science, you need clear and relevant topics that generate the reader’s interest. Here are some Ph.D. topics in computer science you might consider:

Developments in information technology
Is machine learning detrimental to the human workforce?
How to write an algorithm for deep learning
What is the future of 5G in wireless networks
Statistical data in Maths modules in Python
Data retention automation from a website using API
Application of modern programming languages

Looking for computer science topics for research is not easy for an undergraduate. Fortunately, these computer science project topics should make your research paper easy:

Ways of using artificial intelligence in real estate
Discuss reinforcement learning and its applications
Uses of Big Data in science and medicine
How to sort algorithms using Haskell
How to create 3D configurations for a website
Using inverse interpolation to solve non-linear equations
Explain the similarities between the Internet of Things and artificial intelligence

Your dissertation paper is one of the most crucial papers you’ll ever do in your final year. That’s why selecting the best ethics in computer science topics is a crucial part of your paper. Here are some project topics for the computer science final year.

How to incorporate numerical methods in programming
Applications of blockchain technology in cloud storage
How to come up with an automated attendance system
Using dynamic libraries for site development
How to create cubic splines
Applications of artificial intelligence in the stock market
Uses of quantum computing in financial modeling

Your instructor may want you to challenge yourself with an advanced science project. Thus, you may require computer science topics to learn and research. Here are some that may inspire you:

Discuss the best cryptographic protocols
Advancement of artificial intelligence used in smartphones
Briefly discuss the types of security software available
Application of liquid robots in 2023
How to use quantum computers to solve decoherence problem
macOS vs. Windows; discuss their similarities and differences
Explain the steps taken in a cyber security audit

When searching for computer science topics for a seminar, make sure they are based on current research or events. Below are some of the latest research topics in computer science:

How to reduce cyber-attacks in 2023
Steps followed in creating a network
Discuss the uses of data science
Discuss ways in which social robots improve human interactions
Differentiate between supervised and unsupervised machine learning
Applications of robotics in space exploration
The contrast between cyber-physical and sensor network systems

Are you looking for computer science thesis topics for your upcoming projects? The topics below are meant to help you write your best paper yet:

Applications of computer science in sports
Uses of computer technology in the electoral process
Using Fibonacci to solve the functions maximum and their implementations
Discuss the advantages of using open-source software
Expound on the advancement of computer graphics
Briefly discuss the uses of mesh generation in computational domains
How much data is generated from the internet of things?

A computer science presentation requires a topic relevant to current events. Whether your paper is an assignment or a dissertation, you can find your final year computer science project topics below:

Uses of adaptive learning in the financial industry
Applications of transitive closure on graph
Using RAD technology in developing software
Discuss how to create maximum flow in the network
How to design and implement functional mapping
Using artificial intelligence in courier tracking and deliveries
How to make an e-authentication system

Key Computer Science Essay Topics

You may be pressed for time and require computer science master thesis topics that are easy. Below are some topics that fit this description:

What are the uses of cloud computing in 2023
Discuss the server-side web technologies
Compare and contrast android and iOS
How to come up with a face detection algorithm
What is the future of NFTs
How to create an artificial intelligence shopping system
How to make a software piracy prevention algorithm

One major mistake students make when writing their papers is selecting topics unrelated to the study at hand. This, however, will not be an issue if you get topics related to computer science, such as the ones below:

Using blockchain to create a supply chain management system
How to protect a web app from malicious attacks
Uses of distributed information processing systems
Advancement of crowd communication software since COVID-19
Uses of artificial intelligence in online casinos
Discuss the pillars of math computations
Discuss the ethical concerns arising from data mining

We Can Help You with Computer Science Topics, Essays, Thesis, and Research Papers

We hope that this list of computer science topics helps you out of your sticky situation. We do offer other topics in different subjects. Additionally, we also offer professional writing services tailor-made for you.

We understand what students go through when searching the internet for computer science research paper topics, and we know that many students don’t know how to write a research paper to perfection. However, you shouldn’t have to go through all this when we’re here to help.

Don’t waste any more time; get in touch with us today and get your paper done excellently.

Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic.

Overview: CompSci Research Topics

Algorithms & data structures
Artificial intelligence ( AI )
Computer networking
Database systems
Human-computer interaction
Information security (IS)
Software engineering
Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
An evaluation of machine learning algorithms used for recommender systems in streaming services
A review of approximation algorithm approaches for solving NP-hard problems
An analysis of parallel algorithms for high-performance computing of genomic data
The influence of data structures on optimal algorithm design and performance in Fintech
A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
A comparison of streaming algorithm performance for the detection of elephant flows
A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
Exploring the feasibility of applying information theory to feature extraction in retail datasets.
Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

Applying deep learning algorithms for speech recognition in speech-impaired children
A review of the impact of artificial intelligence on decision-making processes in stock valuation
An evaluation of reinforcement learning algorithms used in the production of video games
An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
An analysis of the ethical and social implications of artificial intelligence-based automated marking
The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
An examination of the use of artificial intelligence in orthopaedic surgery
The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

An analysis of the impact of 5G technology on internet penetration in rural Tanzania
Assessing the role of software-defined networking (SDN) in modern cloud-based computing
A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
Exploring the influence of cloud computing on security risks in fintech.
An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
An evaluation of the challenges and opportunities in 6G wireless network adoption
The role of network congestion control algorithms in improving network performance on streaming platforms
An analysis of network coding-based approaches for data security
Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Free Webinar: How To Find A Dissertation Research Topic

Topics & Ideas: Database Systems

An analysis of big data management systems and technologies used in B2B marketing
The impact of NoSQL databases on data management and analysis in smart cities
An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
Exploring the role of data warehousing and business intelligence in global consultancies
An analysis of the use of graph databases for data modelling and analysis in recommendation systems
The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
An examination of the challenges and opportunities of distributed databases in supply chain management
Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
An exploration of how artificial intelligence is changing human-computer interaction patterns in children
An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
Assessing the influence of virtual and augmented reality on consumer purchasing patterns
An examination of the use of gesture-based interfaces in architecture
Exploring the impact of ease of use in wearable technology on geriatric user
Evaluating the ramifications of gamification in the Metaverse
A systematic review of user experience (UX) design advances associated with Augmented Reality
A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

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Topics & Ideas: Information Security

A bibliometric review of current trends in cryptography for secure communication
An analysis of secure multi-party computation protocols and their applications in cloud-based computing
An investigation of the security of blockchain technology in patient health record tracking
A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
A systematic review of secure data storage solutions used for cloud computing in the fintech industry
An analysis of intrusion detection and prevention systems used in the healthcare sector
Assessing security best practices for IoT devices in political offices
An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
A comparative study of digital signature schemes adoption in property transfers
An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

A study of agile software development methodologies and their impact on project success in pharmacology
Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
A study of the impact of DevOps practices on software development and delivery in the healthcare sector
An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
An investigation of software testing techniques and methodologies for subscription-based offerings
A review of software security practices and techniques for protecting against phishing attacks from social media
An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
Exploring the impact of software development outsourcing on project success in multinational contexts
An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

An array-based optimization framework for query processing and data analytics (Chen, 2021)
Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
Embedding constructural documentation in unit tests (Nassif, 2019)
PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
A state-based approach to context modeling and computing (Yue, 2019)
A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Best Computer Science Project Topics: Explained

Discover a wide range of Computer Science Project Topics explained in detail. This comprehensive blog helps students and researchers explore exciting project ideas, providing insights and inspiration for successful projects in the field of Computer Science.

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If you are in search of Computer Science Project Topics, this collection is just what you need to kickstart your journey. Discover a diverse collection of Computer Science Project Topics suitable for academic assignments, research projects, and real-world applications.

Table of Contents

1) Best Computer Science Project Topics

a) Face detection

b) Crime rate prediction

c) E-authentication system

d) Online auction system

e) Evaluation of academic performance

f) Symbol recognition

g) Weather forecasting application

h) Public News Droid

i) Online eBook master

j) Mobile wallet and merchant payment system

2) Conclusion

Best Computer Science Project Topics

Face detection

It holds significant importance and serves various functions across multiple domains. Face detection technology has significantly enhanced the surveillance capabilities of authorities.

The fusion of face detection with biometrics and security technology has facilitated the recognition of individuals' facial features. It has enabled various processes, such as launching an application, ensuring security, and guiding the subsequent steps within an application.

Face detection technology employs facial algorithms to determine the extent of facial patterns. It possesses the capability to adapt and discern which facial attributes to identify and which to disregard.

One of the most promising computer science mini-project ideas for hands-on experimentation is the development of face detection software. This project involves creating a face detection program using the OpenCV library. The program is designed to detect faces in real time, whether from a webcam feed or video files stored on a local PC. Pre-trained XML classifiers are employed to detect and track faces, and you can extend its functionality to identify various objects using different classifiers.

To execute this program successfully, it is necessary to install the OpenCV library on your local machine and configure the paths for the XML classifier files appropriately.

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Crime rate prediction

One of the most innovative computer science ideas is to develop a crime rate prediction system. As the name implies, this computer science project involves creating a system capable of analysing and forecasting crime rates in specific locations.

To function effectively, the system requires relevant data. It employs the K-means data mining algorithm for crime rate prediction. The K-means algorithm is adept at clustering co-offenders and organised crime groups by identifying pertinent crime patterns through hidden links, link prediction, and statistical analysis of crime data.

Crime rate prediction offers numerous advantages, including preemptive measures, culprit tracking, and informed decision-making. This methodology empowers decision-makers to foresee criminal activity and take law enforcement actions to minimise its consequences.

In doing so, stakeholders can enhance public satisfaction, elevate the quality of life, and, most importantly, identify negative externalities, enabling them to take corrective measures. Relevant agencies can optimise their resource utilisation. The crime prediction system expedites the dispensation of justice and contributes to reduced crime rates.

E-authentication system

Various authentication methods, such as OTPs, passwords, and biometrics, are available. These authentication systems enhance user experiences by eliminating the need for multiple setups and bolstering security, thus encouraging more users to embrace the technology.

E-authentication has gained widespread acceptance, serving purposes like accessing government services, online transactions, and various platforms. Users can safeguard their identities with e-authentication, offering a higher level of security.

This project is dedicated to constructing an e-authentication system which combines QR codes and OTPs to fortify security. It aims to prevent unauthorised access due to activities like shoulder surfing and misuse of login credentials. To use this system, users must initially register by providing essential details.

After registration, users can access the login module to authenticate their accounts using the email ID and password created during registration. Subsequently, users can choose between two authentication methods: QR (Quick Response) codes or OTPs (One-Time Passwords). Depending on the user's choice, the system generates either a QR code sent to the user's email, or an OTP delivered via SMS to the registered mobile number.

The system generates QR codes and OTPs randomly during login, enhancing security. However, it requires a consistent Internet connection for operation.

Online auction system

The online auction platform enables users to participate in auctions from any location, granting sellers the opportunity to showcase their products to a global audience.

Another valuable aspect of online auctions is the real-time feedback mechanism, which allows bidders to monitor price fluctuations as bids increase.

Buyers and bidders from around the world can log in at their convenience, irrespective of geographical time differences, ensuring they take advantage of opportunities.

In an online auction, buyers engage in transactions through competitive bidding, with each item having a starting price and a set closing time. The highest bidder for an item is declared the winner and becomes the item's owner.

This project involves the development of a secure online auction system employing a fraud detection method based on binary classification. To participate in an online auction, users are required to provide identification details such as PAN numbers, email addresses, license numbers, etc.

The system then screens, authenticates, and authorises users. Only authorised users are permitted to place bids. The system is designed to detect potential fraudulent users at an early stage, mitigating the risk of online fraud and scams. These introductory-level computer science projects are instrumental in establishing a strong foundation in fundamental programming concepts.

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Evaluation of academic performance

Assessing academic performance serves as a means for educational institutions to monitor student progress. This not only contributes to enhancing individual student achievements but also aids in refining teaching methods and evaluating teacher effectiveness.

Educators can strategically outline teaching objectives to facilitate goal attainment. By doing so, teachers can identify and implement effective pedagogical techniques while discarding those that do not significantly benefit student performance.

One of the most captivating computer science project ideas entails creating an evaluation system capable of analysing students' academic performance using fuzzy logic. In this approach, three key parameters, namely attendance, internal marks, and external marks, are considered to determine the overall academic performance of a student. The application of fuzzy inference systems yields more precise results compared to conventional evaluation techniques.

Throughout the development of this computer science project, it is imperative to ensure that the accuracy of student information uploaded is maintained, devoid of any errors. Faulty data entry could result in inaccurate outcomes.

Symbol recognition

This computer science project is an outstanding choice for beginners. The project's objective is to develop a system capable of identifying symbols provided by the user. This symbol recognition system harnesses an image recognition algorithm to process images and detect symbols. Initially, the system converts RGB objects into grayscale images, which are subsequently transformed into black-and-white images.

Throughout this process, image processing techniques are employed to eliminate unwanted elements and environmental disturbances. The system also utilises optical character recognition, achieving an accuracy rate of 60-80 per cent.

Within this system, a designated directory stores all symbol templates. The images are of fixed size, ensuring accurate symbol recognition. These templates are maintained in a black-and-white format, and the system creates a dataset from them.

When a user inputs a query image into the system, it resizes the image, compares the resized image values to those of the template images in the dataset, and ultimately presents the results in textual format. Thus, while the system accepts image inputs, it provides output in a text-based format.

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Weather forecasting application

This is a beginner-level web development and programming app that will serve best as a project topic for CSE students. The main objective of the app is to create a web-based weather application that can provide real-time weather details (like current temperature and chances of rain) of a particular location. The app can also predict if the day will be rainy, cloudy, or sunny.

Developing a weather forecasting app is the best way to put your coding skills to the test. To create a weather forecasting app, you will need a stronghold on the basics of Web Development, HTML, CSS, and JavaScript. To provide the best backend performance, good knowledge of Node.js and express technologies is a must.

It is important to know how to use API calls to scoop out weather information from other websites and display relevant information in your app.

For the app’s best User Interface, you have to place an input text box in which the users can enter the location for which weather information is needed. As soon as the search button is hit, the weather forecast for the input location should pop out.

Public News Droid

Public News Droid offers various advantages, including:

1) User-friendly navigation

2) Real-time updates

3) Comprehensive news coverage

4) Exclusive access for registered users

5) Reporting mechanism for malicious or irrelevant news

The system comprises two primary modules, one for administrators and one for users. Administrators oversee the accuracy and relevance of news and information. In cases of fake news or misuse, administrators can take corrective action to prevent the dissemination of irrelevant information.

Users, on the other hand, can access news and informative content specific to their respective localities, towns, or cities and contribute news related to other locations.

To use the application, users must complete the registration process and provide the necessary details. Once registered, users gain access to the latest news, the ability to refresh the app for updates, browse additional information, add news articles, and more. Users can also incorporate images and headlines for the news they submit. Mentioning computer science projects on your resume can make it stand out among others.

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Search engine

The search engine proves incredibly valuable by enhancing brand visibility, enabling targeted advertising, boosting brand awareness, managing performance, and increasing website traffic, among other benefits.

Brands can expand their visibility by employing appropriate keywords and various strategies. They can harness the search engine's capabilities to outperform competitors and advance their business.

Enhanced brand visibility not only fosters authenticity but also drives revenue growth for the brand. This search engine is constructed using web annotation, representing one of the current trends in computer science projects. When users input specific words or phrases into the search engine, it automatically retrieves the most relevant pages containing those keywords, thanks to web annotation.

Web annotation greatly contributes to creating user-friendly applications, allowing users to add, modify, or remove information from web resources without altering the resources themselves.

This project utilises web annotation for both pages and images. When users input words, names, or phrases, the system retrieves information and images with corresponding annotations, presenting a list of results matching the user's input. Developing an effective algorithm is essential for generating query result pages or search result records based on user queries in this search engine.

Online eBook master

It is a compelling choice to delve into the development of an online eBook creator. This web-based eBook maker empowers users to design and generate eBooks without incurring any costs. The system consists of two key modules: an admin login and an author login. The admin functions encompass receiving user (author) requests, verifying their credentials, assessing finished eBooks, and fulfilling requests by dispatching the eBooks to the authors.

Users can register in the system via the author login. Upon providing essential information, users gain the capability to craft new books. They can define the book's content, title, page count, incorporate a book cover, and more.

Returning users can log in with their credentials and choose to either create new books or continue editing previously initiated (unfinished) eBooks. Authors are permitted to maintain a maximum of three incomplete eBooks concurrently, with the requirement to finalise at least one book before initiating a new project.

Mobile wallet and merchant payment system

The mobile wallet offers a range of advantages, including:

1) Cashless transactions

2) Password protection for application security

3) QR code generation for secure transactions

4) Storage of funds in merchant's wallet, with transfer to bank accounts

5) Enhanced fraud prevention

The objective behind developing this app is to establish a secure, dependable, and efficient platform for financial transactions. The system generates unique QR code IDs for each transaction, and all passwords are encrypted using the AES Encryption Algorithm.

This application comprises two components: an Android application for merchants to scan QR codes and a consumer application for generating QR codes. The front-end development employs Android Studio, while the back end is supported by SQL Server.

Conclusion

This blog has presented a collection of innovative and captivating Computer Science Project Topics. You can use these ideas as a foundation to create a project. From Artificial Intelligence and Machine Learning to practical solutions in Cybersecurity and Web Development, these projects empower individuals to develop critical skills, expand their knowledge, and address real-world challenges.

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Engineering Mathematics
Discrete Mathematics
Operating System
Computer Networks
Digital Logic and Design
C Programming
Data Structures
Theory of Computation
Compiler Design
Computer Org and Architecture
Learn Data Structures and Algorithms | DSA Tutorial
10 Most Beautiful Women in the World 2024
Sorting Algorithms
Top 10 Most Handsome Men in the World 2024
Graph Data Structure And Algorithms
Binary Search Tree
50+ Happy Anniversary Wishes: Quotes & Status for Wedding Anniversary
List of Generation Names Year Wise: Gen Z, Millennials, Baby Boomers, Alpha Generation
SQL Tutorial
JavaScript Tutorial
10 Best Torrent Sites (2024)
Stack Data Structure
Dynamic Programming or DP
HTML Tutorial
How To Find a Song by Humming: Hum To Search on Google
Searching Algorithms
List of Top Hottest Place in India 2024
Heap Data Structure
Top 10 Highest Paid Actors In The World: From Dwayne Johnson to Akshay Kumar (Complete List)
Queue Data Structure
Aptitude Questions and Answers
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Getting Started with Python Programming
Java Exercises - Basic to Advanced Java Practice Programs with Solutions

Computer Science Projects

Computer science is a popular topic of study today, with numerous applications spanning a wide range. Final-year students frequently find it difficult to select the appropriate computer science project. On the final day of graduation, projects are the only thing that matters. Any IT-related industry where projects have a substantial impact can be chosen for a job or further education. Project work indicates knowledge depth as well as some soft skills like creativity and problem-solving. Your interview prospects will also improve as a result of your final year projects. As a result, in their last year of graduation, students are required to complete a project.

Best Domain to Choose for Conducting the Projects

Artificial intelligence
Web Technology
Data Science
Machine Learning

Recent Project Articles !

C++ Projects
Java Projects
Python Projects
Project Ideas
Department Store Management System(DSMS) using C++
Test Cases For Signup Page Using C Language
Shopping Cart Project Using C Language
OpenCV C++ Program for Face Detection
OpenCV C++ Program for coin detection
OpenCV C++ Program to blur an image
OpenCV C++ Program to create a single colored blank image
OpenCV C++ Program to blur a Video
OpenCV C++ Program to play a video
Creating a PortScanner in C
Student Data Management in C++
OpenGL program for Simple Ball Game
Implementation of Minesweeper Game
Finding cabs nearby using Great Circle Distance formula
Program to remotely Power On a PC over the internet using the Wake-on-LAN protocol.

Java Projects :

A Group chat application in Java
Generating Password and OTP in Java
Creative Programming In Processing | Set 1 (Random Walker)
Creative Programming In Processing | Set 2 (Lorenz Attractor)

Python Projects :

Make Notepad using Tkinter
Color game using Tkinter in Python
Python | Message Encode-Decode using Tkinter
XML parsing in Python
Desktop Notifier in Python
Hangman Game in Python
Junk File Organizer in Python
Browser Automation Using Selenium
Tracking bird migration using Python-3
Twitter Sentiment Analysis using Python
Image Classifier using CNN
Implementing Photomosaics
Working with Images in Python
OpenCV Python Program to blur an image
Opencv Python program for Face Detection
Cartooning an Image using OpenCV – Python
OpenCV Python Program to analyze an image using Histogram
OpenCV Python program for Vehicle detection in a Video frame
DNA to Protein in Python 3
Viruses – From Newbie to pro
Handling Ajax request in Django
Working with zip files in Python
Morse Code Translator In Python
Simple Chat Room using Python
Creating a Proxy Webserver in Python | Set 1
Creating a Proxy Webserver in Python | Set 2
Project Idea | Audio to Sign Language Translator
Understanding Code Reuse and Modularity in Python 3
Multi-Messenger : A python project, messaging via Terminal
Movie recommendation based on emotion in Python
Implementing Web Scraping in Python with BeautifulSoup
Computer Vision module application for finding a target in a live camera

Web Development Projects

Design an Event Webpage using HTML & CSS
Design a Parallax Webpage using HTML & CSS
Design a Webpage like Technical Documentation using HTML & CSS
Design Homepages like Facebook using HTML and CSS
Page for online food delivery system using HTML and CSS
Responsive sliding login and registration forms using HTML CSS and JavaScript?
Design a Student Grade Calculator using JavaScript
Slide Down a Navigation Bar on Scroll using HTML, CSS, and JavaScript
Design a BMI Calculator using JavaScript
Task Tracker Project

Project Ideas :

Project Idea | (Static Code Checker for C++)
Project Idea | (Dynamic Hand Gesture Recognition using neural network)
Project Idea | God’s Eye
Project Idea | (Ca-solutions)
Project Idea | College Connect
Project Idea | Empower Illiterate
Project Idea | (Remote Lab Assistance)
Project Idea | (Project Approval System)
Project Idea | (Online Course Registration)
Project Idea | (Universal Database Viewer)
Project Idea | Sun Rise/Set Time Finder
Project Idea | Automatic Youtube Playlist Downloader
Project Idea | Aadhaar Thumb: A Platform to All Services
Project Idea | (Health services & Medical outcome monitoring)
Project Idea| (Magical Hangouts: An Android Messaging App)
Project Idea | JamFree
Project Idea | AI Therapist
Project Idea | Get Your Logo
Project Idea | ( Client Master)
Project Idea | (A Game of Anagrams )
Project Idea | Breakout game in Python
Project Idea | (Games using Hand Gestures)
Project Idea | Amanda: A Smart Enquiry Chatbot
Project Idea | (A.T.L.A.S: App Time Limit Alerting System)
Project Idea | Sign Language Translator for Speech-Impaired
Project Idea | Personality Analysis using hashtags from tweets
Project Idea | Recommendation System based on Graph Database
Creating a C/C++ Code Formatting tool with help of Clang tools
Project Idea (Augmented Reality – QR Code Scanner)
Project Idea (Augmented Reality – ARuco Code Detection and Estimation)
Project Idea | (CSE Webnode)
Project Idea | College Network
Project Idea | (Online UML Designing Tool)
Project Idea | Voice Based Email for Visually Challenged
Project Idea | Assist Bot
Project Idea | Social-Cop
Project Idea | MediTrack
Project Idea | (CAPTURED)
Project Idea | LinkBook
Project Idea | (Trip Planner)
Project Idea | EveMythra Bot
Project Idea | Green Rides
Project Idea | E-Ration Shop
Project Idea | Smart Elevator
Project Idea | Get Me Through
Project Idea | Innovate Email
Project Idea | NextVAC Platform
Project Idea | League of Fitness
Project Idea | (A Personal Assistant)
Project Idea | (Smart Restaurants)
Project | Scikit-learn – Whisky Clustering
Creating a Calculator for Android devices
Project Idea | Airport Security Using Beacon
Project Experience | (Brain Computer Interface)
Project Idea | ( True Random Number Generator)
Project Idea | Distributed Downloading System
Project Idea | (Personalized real-time update system)
Project Idea | Attendance System Using Smart Card
Project Idea | (Detection of Malicious Network activity)
Project Idea | Smart Waste Management System
Project Idea – Bio-Hashing : Two factor authentication
Project Idea | noteSort (Classify handwritten notes)
Project Idea | Health Application powered by IBM Watson
Project Idea | Collaborative Editor Framework in Real Time
Project Idea | Department Data Analysis Mobile Application
Project Idea | Analysis of Emergency 911 calls using Association Rule Mining
Crop monitoring and smart farming using IoT
MyHelper (Access your phone from anywhere without Internet)
Project Idea | (Robust Pedestrian detection)
Project Idea | ( Character Recognition from Image )
Project Idea | (Model based Image Compression of Medical Images)
Project Idea | Motion detection using Background Subtraction Techniques
Project Idea | (Optimization of Object-Based Image Analysis with Super-Pixel for Land Cover Mapping)
A Number Link Game
Designing Use Cases for a Project
Building a Basic Chrome Extension
How to write a good SRS for your Project
Creating WYSIWYG Document Editor | Natural Language Programming

Computer Science – FAQs

1. what is computer science .

Computer science (CS) is the study of computers and algorithmic processes including their principles, their hardware and software designs, their applications, and their impact on society.

2. Which is the best project in the final year?

The best final-year project is subjective and depends on your interests and skills. Choose a project that appeals to your interests, challenges you, and provides real learning possibilities.

3. How do I choose a major project for CSE?

To choose a major project for Computer Science Engineering (CSE), follow these steps: Identify your interests and strengths within CSE. Research current trends and emerging technologies in the field. Discuss project ideas with professors, peers, and industry professionals. Consider the project’s feasibility, scope, and potential impact. Select a project that excites you and aligns with your academic goals.

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The Top 10 Most Interesting Computer Science Research Topics

Computer science touches nearly every area of our lives. With new advancements in technology, the computer science field is constantly evolving, giving rise to new computer science research topics. These topics attempt to answer various computer science research questions and how they affect the tech industry and the larger world.

Computer science research topics can be divided into several categories, such as artificial intelligence, big data and data science, human-computer interaction, security and privacy, and software engineering. If you are a student or researcher looking for computer research paper topics. In that case, this article provides some suggestions on examples of computer science research topics and questions.

Find your bootcamp match

What makes a strong computer science research topic.

A strong computer science topic is clear, well-defined, and easy to understand. It should also reflect the research’s purpose, scope, or aim. In addition, a strong computer science research topic is devoid of abbreviations that are not generally known, though, it can include industry terms that are currently and generally accepted.

Tips for Choosing a Computer Science Research Topic

Brainstorm . Brainstorming helps you develop a few different ideas and find the best topic for you. Some core questions you should ask are, What are some open questions in computer science? What do you want to learn more about? What are some current trends in computer science?
Choose a sub-field . There are many subfields and career paths in computer science . Before choosing a research topic, ensure that you point out which aspect of computer science the research will focus on. That could be theoretical computer science, contemporary computing culture, or even distributed computing research topics.
Aim to answer a question . When you’re choosing a research topic in computer science, you should always have a question in mind that you’d like to answer. That helps you narrow down your research aim to meet specified clear goals.
Do a comprehensive literature review . When starting a research project, it is essential to have a clear idea of the topic you plan to study. That involves doing a comprehensive literature review to better understand what has been learned about your topic in the past.
Keep the topic simple and clear. The topic should reflect the scope and aim of the research it addresses. It should also be concise and free of ambiguous words. Hence, some researchers recommended that the topic be limited to five to 15 substantive words. It can take the form of a question or a declarative statement.

What’s the Difference Between a Research Topic and a Research Question?

A research topic is the subject matter that a researcher chooses to investigate. You may also refer to it as the title of a research paper. It summarizes the scope of the research and captures the researcher’s approach to the research question. Hence, it may be broad or more specific. For example, a broad topic may read, Data Protection and Blockchain, while a more specific variant can read, Potential Strategies to Privacy Issues on the Blockchain.

On the other hand, a research question is the fundamental starting point for any research project. It typically reflects various real-world problems and, sometimes, theoretical computer science challenges. As such, it must be clear, concise, and answerable.

How to Create Strong Computer Science Research Questions

To create substantial computer science research questions, one must first understand the topic at hand. Furthermore, the research question should generate new knowledge and contribute to the advancement of the field. It could be something that has not been answered before or is only partially answered. It is also essential to consider the feasibility of answering the question.

2. The Influence of Extraction Methods on Big Data Mining

Data mining has drawn the scientific community’s attention, especially with the explosive rise of big data. Many research results prove that the extraction methods used have a significant effect on the outcome of the data mining process. However, a topic like this analyzes algorithms. It suggests strategies and efficient algorithms that may help understand the challenge or lead the way to find a solution.

3. Integration of 5G with Analytics and Artificial Intelligence

According to the International Finance Corporation, 5G and AI technologies are defining emerging markets and our world. Through different technologies, this research aims to find novel ways to integrate these powerful tools to produce excellent results. Subjects like this often spark great discoveries that pioneer new levels of research and innovation. A breakthrough can influence advanced educational technology, virtual reality, metaverse, and medical imaging.

4. Leveraging Asynchronous FPGAs for Crypto Acceleration

To support the growing cryptocurrency industry, there is a need to create new ways to accelerate transaction processing. This project aims to use asynchronous Field-Programmable Gate Arrays (FPGAs) to accelerate cryptocurrency transaction processing. It explores how various distributed computing technologies can influence mining cryptocurrencies faster with FPGAs and generally enjoy faster transactions.

5. Cyber Security Future Technologies

Cyber security is a trending topic among businesses and individuals, especially as many work teams are going remote. Research like this can stretch the length and breadth of the cyber security and cloud security industries and project innovations depending on the researcher’s preferences. Another angle is to analyze existing or emerging solutions and present discoveries that can aid future research.

6. Exploring the Boundaries Between Art, Media, and Information Technology

The field of computers and media is a vast and complex one that intersects in many ways. They create images or animations using design technology like algorithmic mechanism design, design thinking, design theory, digital fabrication systems, and electronic design automation. This paper aims to define how both fields exist independently and symbiotically.

7. Evolution of Future Wireless Networks Using Cognitive Radio Networks

This research project aims to study how cognitive radio technology can drive evolution in future wireless networks. It will analyze the performance of cognitive radio-based wireless networks in different scenarios and measure its impact on spectral efficiency and network capacity. The research project will involve the development of a simulation model for studying the performance of cognitive radios in different scenarios.

8. The Role of Quantum Computing and Machine Learning in Advancing Medical Predictive Systems

In a paper titled Exploring Quantum Computing Use Cases for Healthcare , experts at IBM highlighted precision medicine and diagnostics to benefit from quantum computing. Using biomedical imaging, machine learning, computational biology, and data-intensive computing systems, researchers can create more accurate disease progression prediction, disease severity classification systems, and 3D Image reconstruction systems vital for treating chronic diseases.

9. Implementing Privacy and Security in Wireless Networks

Wireless networks are prone to attacks, and that has been a big concern for both individual users and organizations. According to the Cyber Security and Infrastructure Security Agency CISA, cyber security specialists are working to find reliable methods of securing wireless networks . This research aims to develop a secure and privacy-preserving communication framework for wireless communication and social networks.

10. Exploring the Challenges and Potentials of Biometric Systems Using Computational Techniques

Much discussion surrounds biometric systems and the potential for misuse and privacy concerns. When exploring how biometric systems can be effectively used, issues such as verification time and cost, hygiene, data bias, and cultural acceptance must be weighed. The paper may take a critical study into the various challenges using computational tools and predict possible solutions.

Computer Research Questions

Why are there so many programming languages?
Is there a better way to enhance human-computer interactions in computer-aided learning?
How safe is cloud computing, and what are some ways to enhance security?
Can computers effectively assist in the sequencing of human genes?
How valuable is SCRUM methodology in Agile software development?

Choosing the Right Computer Science Research Topic

Computer science research is a vast field, and it can be challenging to choose the right topic. There are a few things to keep in mind when making this decision. Choose a topic that you are interested in. This will make it easier to stay motivated and produce high-quality research for your computer science degree .

Select a topic that is relevant to your field of study. This will help you to develop specialized knowledge in the area. Choose a topic that has potential for future research. This will ensure that your research is relevant and up-to-date. Typically, coding bootcamps provide a framework that streamlines students’ projects to a specific field, doing their search for a creative solution more effortless.

Computer Science Research Topics FAQ

To start a computer science research project, you should look at what other content is out there. Complete a literature review to know the available findings surrounding your idea. Design your research and ensure that you have the necessary skills and resources to complete the project.

The first step to conducting computer science research is to conceptualize the idea and review existing knowledge about that subject. You will design your research and collect data through surveys or experiments. Analyze your data and build a prototype or graphical model. You will also write a report and present it to a recognized body for review and publication.

You can find computer science research jobs on the job boards of many universities. Many universities have job boards on their websites that list open positions in research and academia. Also, many Slack and GitHub channels for computer scientists provide regular updates on available projects.

There are several hot topics and questions in AI that you can build your research on. Below are some AI research questions you may consider for your research paper.

Will it be possible to build artificial emotional intelligence?
Will robots replace humans in all difficult cumbersome jobs as part of the progress of civilization?
Can artificial intelligence systems self-improve with knowledge from the Internet?

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Research projects.

The CS department has resources available for research projects. The following is a quick start guide to research projects in Computer Science Department. This quick start guide does not cover all topics and it is recommended that you consult the CS Guide for more information.

This guide is designed to help those beginning a research project by pointing to appropriate sections of the CS Guide for typical start-up tasks. Research projects typically need the following: storage space that can be shared by members of the research group, a web presence (possibly driven by a back-end database), mailing lists, code/document repositories. Here is how each of these are implemented and requested in the Computer Science Department.

Project Disk Space - We encourage projects (even single-person projects) to use disk space outside of the user home directory filesystem. This has several benefits. First, the quota is separate from any particular project member and can be much larger than we allow for home directories. Second, project members can be added and removed to change access without moving the files themselves. Third, users can collaborate and share files without having to give others access to their home directory. Finally, by keeping projects in separate partitions, CS Staff can manage our storage more efficiently. For more details, please see the Disk Space page. To request disk space, use the "Project Disk Space" form link on the left. Note that if you specify additional project members in the request form, we will automatically create a unix group consisting of you and the listed users and set the setgid flag on the project directory.
Project Web Space - To set-up a web page or web site for the project, first request project disk space and then use the "Project Web Space" form to the left to request that a subdirectory of the project space be mapped to a web URL. Project web space will give you the ability to host your research group or project-related content at its own subdomain (e.g. http://project.cs.princeton.edu/ ). Even if you are only requesting project disk space for the sole purpose of hosting a project web site, we recommend that you choose a subdirectory (e.g., public_html ) within the project disk space. This will give you the flexibility in the future to also use the project disk space for other purposes.
Project Database - If your project needs a MySQL database (perhaps as a back-end store for a web site), use the "Database" request form at the left and specify a collaborative database.
Mailing Lists - Research projects typically create one or more mailing lists to manage their communication.
Source Repository - If your group will be collaboratively developing code or writing papers, you may want to request an SVN repository from OIT (requires Princeton OIT authentication).
Rack Space for Servers - If you have physical rack-mount servers, they can be housed either in Room 002 of the CS Building or at the University data center at 151 Forrestal . Contact CS Staff for availability and additional details.
Role Accounts / Mail Aliases - please note that we do not create role accounts or provide email aliases. By properly configuring access control, role accounts should not be necessary. Email aliases can be mimicked by requesting a mailing list and selecting the "Mail Alias" type in the form.
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Department of Computer Science Room 226 35 Olden Street, Princeton, NJ 08540

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Research projects

Find a postgraduate research project in your area of interest by exploring the research projects that we offer in the Department of Computer Science.

We have a broad range of research projects for which we are seeking doctoral students. Browse the list of projects on this page or follow the links below to find information on doctoral training opportunities, or applying for a postgraduate research programme.

Doctoral training opportunities
How to apply

Alternatively, if you would like to propose your own project then please include a research project proposal and the name of a possible supervisor with your application.

Available projects

List by research theme List by supervisor

Future computing systems projects

A Multi-Tenancy FPGA Cloud Infrastructure and Runtime System
A New Generation of Terahertz Emitters: Exploiting Electron Spin
Balancing security and privacy with data usefulness and efficiency in wireless sensor networks
Blockchain-based Local Energy Markets
Cloud Computing Security
Design and Exploration of a Memristor-enabled FPGA Architecture
Design and Implementation of an FPGA-Accelerated Data Analytics Database
Designing Safe & Explainable Neural Models in NLP
Dynamic Resource Management for Intelligent Transportation System Applications
Evaluating Systems for the Augmentation of Human Cognition
Exploring Unikernel Operating Systems Running on reconfigurable Softcore Processors
Finding a way through the Fog from the Edge to the Cloud
Guaranteeing Reliability for IoT Edge Computing Systems
Hardware Aware Training for AI Systems
Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
Machine Learning with Bio-Inspired Neural Networks
Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
Pervasive Technology for Multimodal Human Memory Augmentation
Power Management Methodologies for IoT Edge Devices
Power Transfer Methods for Inductively Coupled 3-D ICs
Problems in large graphs representing social networks
Programmable Mixed-Signal Fabric for Machine Learning Applications
Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
Security and privacy in p2p electricity trading
Skyrmion-based Electronics
Smart Security for Smart Services in an IoT Context
Spin waves dynamics for spintronic computational devices
Technology-driven Human Memory Degradation
Ultrafast spintronics with synthetic antiferromagnets

Human centred computing projects

Advising on the Use and Misuse of Collaborative Coding Workflows
Automatic Activity Analysis, Detection and Recognition
Automatic Emotion Detection, Analysis and Recognition
Automatic Experimental Design with Human in the Loop (2025 entry onward)
Biases in Physical Activity Tracking
Computer Graphics - Material Appearance Modeling and Physically Based Rendering
Design principles for glancing at information by visually disabled users
Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
Learning of user models in human-in-the-loop machine learning (2025 entry onward)
Machine Learning and Cognitive Modelling Applied to Video Games
Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
Music Generation and Information Processing via Deep Learning
Understanding the role of the Web on Memory for Programming Concepts
User Modeling for Physical Activity Tracking

Artificial intelligence projects

(MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
Abstractive multi-document summarisation
Applying Natural Language Processing to real-world patient data to optimise cancer care
Automated Repair of Deep Neural Networks
Automatic Learning of Latent Force Models
Biologically-Plausible Continual Learning
Cognitive Robotics and Human Robot Interaction
Collaborative Probabilistic Machine Learning (2025 entry onward)
Computational Modelling of Child Language Learning
Contextualised Multimedia Information Retrieval via Representation Learning
Controlled Synthesis of Virtual Patient Populations with Multimodal Representation Learning
Data Integration & Exploration on Data Lakes
Data Lake Exploration with Modern Artificial Intelligence Techniques
Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
Deep Learning for Temporal Information Processing
Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
Event Coreference at Document Level
Explainable and Interpretable Machine Learning
Formal Verification for Robot Swams and Wireless Sensor Networks
Formal Verification of Robot Teams or Human Robot Interaction
Foundations and Advancement of Subontology Generation for Clinically Relevant Information
Generating Goals from Responsibilities for Long Term Autonomy
Generating explainable answers to fact verification questions
Integrated text and table mining
Interpretable machine learning for healthcare applications
Knowledge Graph Construction via Learning and Reasoning
Knowledge Graph for Guidance and Explainability in Machine Learning
Machine Learning for Vision and Language Understanding
Multi-task Learning and Applications
Neuro-sybolic theorem proving
Ontology Informed Machine Learning for Computer Vision
Optimization and verification of systems modelled using neural networks
Probabilistic modelling and Bayesian machine learning (2025 entry onward)
Representation Learning and Its Applications
Software verification with contrained Horn clauses and first-order theorem provers
Solving PDEs via Deep Neural Nets: Underpinning Accelerated Cardiovascular Flow Modelling with Learning Theory
Solving mathematical problems using automated theorem provers
Solving non-linear constraints over continuous functions
Symmetries and Automated Theorem Proving
Text Analytics and Blog/Forum Analysis
Theorem Proving for Temporal Logics
Trustworthy Multi-source Learning (2025 entry onward)
Verification Based Model Extraction Attack and Defence for Deep Neural Networks
Zero-Shot Learning and Applications

Software and e-infrastructure projects

Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
Component-based Software Development.
Effective Teaching of Programming: A Detailed Investigation
Exploiting Software Vulnerabilities at Large Scale
Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
Using Program Synthesis for Program Repair in IoT Security
Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars

Theory and foundations projects

Application Level Verification of Solidity Smart Contracts
Categorical proof theory
Formal Methods: Hybrid Event-B and Rodin
Formal Methods: Mechanically Checking the Semantics of Hybrid Event-B
Formal Semantics of the Perfect Language
Mathematical models for concurrent systems

James Elson projects

Data science projects.

Data Wrangling
Fishing in the Data Lake
Specifying and Optimising Data Wrangling Tasks

Sophia Ananiadou projects

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Computing Research News

This article is published in the October 2022 issue.

On Undergraduate Research in Computer Science: Tips for shaping successful undergraduate research projects

Note: Khuller was the recipient of the 2020 CRA-E Undergraduate Research Faculty Mentoring Award , which recognizes individual faculty members who have provided exceptional mentorship, undergraduate research experiences and, in parallel, guidance on admission and matriculation of these students to research-focused graduate programs in computing. CRA-E is currently accepting nominations for the 2023 award program .

One of the goals I hope to accomplish with this article is to open the eyes of faculty to the ways in which bright and motivated undergraduates can contribute meaningfully to their research projects and groups. This piece intends to help educate folks who have limited experience with undergraduate research or are unsure how to come up with research projects. I hope it helps others learn quickly from the knowledge I have gained over the years.

Exposing undergraduates to research may encourage them to pursue PhDs At the CRA Conference at Snowbird this summer, data was presented that showed that the overall number of PhDs granted in Computer Science (CS) in the US has not changed substantially in the last decade even though undergraduate programs have grown significantly. Meanwhile, the percentage of US students getting PhDs in CS showed a pretty substantial decline from 48% to 31%. While there are many factors at play–notably a strong job market for undergraduates– I do know from prior discussions with undergraduate students (UGs), that many CS departments also do not make a substantial effort in exposing UGs to research opportunities. Moreover, when I started as a faculty member I too struggled in defining good research projects for undergraduates (they were either too easy or too similar to PhD research topics, and so were likely not appropriate for undergraduates). I think getting UGs excited about research is perhaps the first step to getting them excited to think about getting a PhD as a career option.

Is research by undergraduate students an oxymoron? I will admit that initially I too was skeptical about the possibility and success of true undergraduate research. My own research experiences as an undergraduate were pathetic. As a student often I would hear people say “I am going to the library to do research”. So I too went to the library to do research. Research to me meant finding something in the library that was not in a textbook, understanding it, and telling people about the work. At that point I thought I had done some research! I never gave much thought to how new material got into journals to begin with.

Talking to a colleague recently – he said “maybe what all UGs do in a chemistry lab is wash test tubes….”. The truth is that I do not really know what UG research in chemistry looks like. But the point I wanted to make with this article is that high level UG research in CS is entirely doable. Indeed, in theoretical computer science (TCS) we have witnessed brilliant papers in top conferences by undergraduate students, and I would argue that UG research can be done quite effectively in other areas of computing research as well.

So what should UG research in CS look like? I have advised over 30 undergraduate researchers and based on my experiences, I have a few observations. Most successful research projects involving undergraduates require a lead time of about 18 months before graduation. It usually takes a few months for the student to read the relevant papers, and for us to identify a topic that aligns with the student’s interests and background. I usually expect that students would have taken both an undergraduate level class in algorithm design as well as discrete mathematics. If they can take a graduate level class, that would also be incredibly valuable.

Tips for shaping successful undergraduate research projects Below is my process for defining a successful UG research project. UGs typically have 12-18 months for a research project, not 3-4 years like most Ph.D. students.

At my first meeting, I ask the students about the different topics they learned about in their Algorithms class and what appealed to them the most.
Using their answer from bullet #1, I usually spend some time thinking about the right topic for them to work on. The key here is that any paper that the student has to read should not have a long chain of preceding papers that will take them months to get to. Luckily many graph problems as well as combinatorial optimization and scheduling problems lend themselves to easy descriptions. So in a few minutes you can describe the problem.
The research should be on a topic of significant interest and related to things I have worked on, and one in which I have some intuition about the direction of research and conjectures that might be true and provable with elementary methods.
I usually treat undergraduates the same way as PhD students, while being aware that they have limited time (a year) as opposed to PhD students who might begin a vaguely defined research project.
Have them work jointly with a PhD student, if the research is close enough to the PhD students interests and expertise. It’s also a valuable mentoring experience for the PhD student. Simply having a couple of undergrads work on a project jointly can be motivating for both.
One benefit of tackling hard problems at this stage is that there is no downside. If a student does not make progress, in the worst case they read a few papers and learn some new things. This allows us to work on problems with less pressure than second and third year graduate students are under.

Over the last 25 years, I have had the opportunity to work with a very large number of talented undergraduates –from University of Maryland (UMD) and Northwestern University, but also many via the NSF funded REU site program (REU CAAR) that Bill Gasarch (UMD) and I co-ran from 2012-2018. Many of the students I advised, have published the work they did and subsequently received fellowships and admission to top Ph.D programs. Recent graduates are Elissa Redmiles (Ph.D. UMD), Frederic Koehler (Ph.D. MIT) and Riley Murray (Ph.D. Caltech). I specifically wanted to mention An Zhu (Ph.D. Stanford University) who first opened my eyes to the amazing work that is possible by undergraduates.

About the Author Samir Khuller received his M.S and Ph.D from Cornell University in 1989 and 1990, respectively, under the supervision of Vijay Vazirani. He was the first Elizabeth Stevinson Iribe Chair for CS at the University of Maryland. As chair he led the development of the Brendan Iribe Center for Computer Science and Innovation, a project completed in March 2019. In March 2019, Khuller joined Northwestern University as the Peter and Adrienne Barris Chair for CS.

His research interests are in graph algorithms, discrete optimization, and computational geometry. He has published about 200 journal and conference papers, and several book chapters on these topics. He served on the ESA Steering Committee from 2012-2016 and chaired the 2019 MAPSP Scheduling Workshop, and served on the program committee’s of many top conferences. From 2018-2021 he was Chair of SIGACT. In 2020, he received the CRA-E Undergraduate Research Mentoring Award and in 2021 he was selected as a Fellow of EATCS.

He received the National Science Foundation’s Career Development Award, several Department Teaching Awards, the Dean’s Teaching Excellence Award and also a CTE-Lilly Teaching Fellowship. In 2003, he and his students were awarded the “Best newcomer paper” award for the ACM PODS Conference. He received the University of Maryland’s Distinguished Scholar Teacher Award in 2007, as well as a Google Research Award and an Amazon Research Award. In 2016, he received the European Symposium on Algorithms inaugural Test of Time Award for his work with Sudipto Guha on Connected Dominating Sets. He graduated at the top of the Computer Science Class from IIT-Kanpur.

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100+ Computer Science Topics: A Comprehensive Guide

Computer Science is a vast and dynamic field that plays a fundamental role in today’s technological landscape. This blog aims to provide an overview of various computer science topics, from core concepts to specialized areas and emerging trends.

Whether you’re a student considering a computer science degree or someone interested in the latest developments in technology, this guide will help you navigate the world of computer science.

What Are The Core Concepts of Computer Science?

Table of Contents

Algorithms and Data Structures

At the heart of computer science lies the study of algorithms and data structures. Algorithms are step-by-step procedures for solving problems, and data structures are the ways we organize and store data.

They are crucial for problem-solving and efficient software development. Understanding algorithms and data structures is fundamental for any computer scientist.

Popular data structures include arrays, linked lists, trees, and hash tables, while common algorithms encompass sorting, searching, and graph algorithms. The data structure and method used can have a big influence on how well software runs.

Programming Languages

Computer science relies on a multitude of programming languages. From classics like C, C++, and Java to modern languages like Python and JavaScript, each language has its strengths and weaknesses.

The choice of programming language is based on the particular task at hand as well as elements like usability, performance, and library accessibility.

Learning multiple languages can make you a versatile programmer and open doors to different job opportunities. For instance, web development often requires JavaScript, while data science frequently employs Python.

How To Select Computer Science Topics?

Selecting computer science topics can be a daunting task, given the vastness of the field. Here are 10 steps to help you choose the right computer science topics:

Identify Your Interests: Start by reflecting on one’s interests within computer science. Are you passionate about artificial intelligence, web development, cybersecurity, or data science? Knowing what excites you will make the selection process more manageable.
Assess Your Knowledge: Consider your current knowledge and experience. If you’re a beginner, you may want to explore foundational topics like algorithms and data structures. For more advanced learners, specialized or emerging topics might be suitable.
Research Current Trends: Stay updated (with trends) on the latest trends and emerging technologies in computer science. Read blogs, research papers, and news articles to understand what’s hot in the field. Topics like blockchain, quantum computing, and AI ethics are currently trending.
Consider Your Career Goals: Think about your long-term career goals. If you aspire to become a data scientist, topics related to machine learning, data analysis, and big data are relevant. Tailor your choices to align with your career aspirations.
Consult with Professors or Mentors: If you’re a student, reach out to your professors or mentors for guidance. They can recommend topics that match your skills and career goals and may even suggest research opportunities.
Explore Core Concepts: Ensure you have a strong foundation by exploring core computer science concepts like algorithms, data structures, and programming languages. These fundamentals are essential for building expertise in other areas.
Assess Practicality: Consider the practicality of the topic. Some topics may have limited real-world applications, while others can lead to tangible projects or research. Choose topics that allow you to apply your knowledge.
Review Project Opportunities: If you’re looking to gain hands-on experience, assess the availability of projects related to your chosen topic. Many universities and online platforms offer project-based courses that can deepen your understanding.
Balance Depth and Breadth: Strive for a balance between depth and breadth. While it’s essential to specialize in a particular area, computer science is an interdisciplinary field, and having a broad understanding can be valuable.
Stay Flexible: Be open to changing your focus over time. As technology evolves, new topics emerge, and your interests may shift. Stay flexible and willing to adapt to the changing landscape of computer science.

Remember that selecting computer science topics is a personal and evolving process.

Your interests, career goals, and knowledge level will influence your choices. Keep learning, exploring, and adapting as you progress in your computer science journey.

Artificial Intelligence and Machine Learning

Neural networks
Reinforcement learning
Natural language processing
Computer vision
Deep learning frameworks

Cybersecurity

Network security
Ethical hacking
Cryptography techniques
Security Protocols
Intrusion detection

Database Management

SQL vs. NoSQL databases
Query optimization
Big Data technologies
Database design principles
Data warehousing

Computer Graphics and Visualization

3D rendering
Animation techniques
Virtual reality (VR)
Augmented reality (AR)
Computer-aided design (CAD)

Quantum Computing

Quantum gates
Quantum algorithms
Quantum cryptography
Quantum hardware
Quantum supremacy

Internet of Things (IoT)

IoT protocols
Smart homes
Industrial IoT
Edge computing
IoT security

Blockchain Technology

Distributed ledger technology
Smart contracts
Cryptocurrency platforms
Blockchain for supply chain

Computer Science Education

Computer science degrees
Online coding bootcamps
Data science courses
AI certifications
MOOC platforms

Career Paths in Computer Science

Software developer roles
Data scientist jobs
Network engineer careers
Cybersecurity analyst positions
Cloud computing specialists

Web Development

Front-end development
Back-end programming
Full-stack development
Responsive web design
Web application frameworks

Operating Systems

Linux distributions
Windows internals
Real-time operating systems
File systems
Process management

Computer Networks

TCP/IP protocol suite
Network topologies
Wireless networks
Network virtualization
SDN and NFV

Software Engineering

Agile methodologies
DevOps practices
Software testing
Code quality and refactoring
Project management tools

Data Science and Big Data

Data preprocessing
Machine learning pipelines
Data visualization tools
Hadoop and Spark
Data analysis techniques

Game Development

Game engines
Unity and Unreal Engine
Game design principles
Game monetization strategies
Mobile game development

Ethical AI and AI Ethics

AI fairness
AI accountability
AI regulations
AI for social good

Human-Computer Interaction (HCI)

Usability testing
User experience (UX) design
HCI principles
User interface (UI) guidelines
Accessibility in HCI

Cloud Computing

Cloud service providers
Infrastructure as a Service (IaaS)
Platform as a Service (PaaS)
Serverless computing
Cloud security
Robotic sensors
Robot control systems
Swarm robotics
Industrial robotics
Humanoid robots

Emerging Trends and Technologies With Computer Science Topics

Utilizing the ideas of quantum physics, quantum computing is an interesting and relatively new topic that allows computations to be completed at rates that are not possible with traditional computers.

Drug research, optimization, and encryption are just a few of the industries that quantum computers have the potential to completely transform. Research in quantum computing is rapidly progressing, with companies like IBM and Google making significant strides.

The network of networked items and gadgets that gather and share data is referred to as the Internet of Things (IoT). From smart homes to industrial sensors, IoT is transforming the way we live and work. However, with the convenience and connectivity IoT offers, come concerns about security and privacy.

In order to solve these issues and guarantee the secure and effective operation of IoT devices, computer scientists will be essential as the Internet of Things grows.

Blockchain technology, known for its association with cryptocurrencies like Bitcoin, is finding applications in various sectors beyond finance. Blockchains provide secure and transparent ledgers for recording transactions and data.

Use cases range from supply chain management and voting systems to intellectual property protection.

As blockchain technology matures, computer scientists will find opportunities to develop innovative solutions and address its scalability and environmental concerns.

Computer Science Education and Career Paths

Computer science degrees and courses.

For those interested in pursuing a career in computer science, there are various educational paths to consider. These include bachelor’s, master’s, and Ph.D. programs, as well as online learning options.

When choosing a program, it’s essential to consider your goals, the curriculum, and the reputation of the institution.

Online learning platforms and coding bootcamps offer flexible options for acquiring computer science skills. They can be a good fit for those looking to pivot into a tech career or acquire specific programming skills.

Career Opportunities in Computer Science

Computer science offers a broad range of career opportunities. Job roles include software developer, data scientist, network engineer, cybersecurity analyst, and AI specialist, among others.

Salaries and job prospects vary depending on the role and your level of experience.

Computer science professionals are in demand in virtually every industry, from technology giants like Google and Amazon to healthcare, finance, and government agencies.

Computer science is a field of limitless potential and continuous growth. It underpins the technology that powers our world and shapes the future.

From the fundamentals of algorithms and data structures to the cutting-edge technologies of AI, quantum computing, and blockchain, computer science is a dynamic and ever-evolving discipline.

Whether you’re a student embarking on a computer science journey or a technology enthusiast exploring the latest trends, the diverse and exciting world of computer science offers something for everyone.

By staying informed and continually learning (with topics like computer science topics), you can contribute to the ongoing transformation of our digital landscape.

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Top 30+ Computer Science Project Topics of 2024 [Source Code]

Home Blog Web Development Top 30+ Computer Science Project Topics of 2024 [Source Code]

Choosing the best computer science project topic is critical to the success of any computer science student or employee. After all, the more engaging and interesting topic, the more likely it is that students or employees will be able to stay motivated and focused throughout the duration of the project. However, with so many options out there, it can be tough to decide which one is right for you.

To help you get started, I have compiled a list of best computer science project topics for students and professionals like myself. These ideas cover everything from machine learning algorithms to data mining techniques, promising to be both challenging and engaging. If staying current with the latest trends is a bit tricky while brainstorming computer science project topics, I'd recommend opting for the best online course in Web Development . The coursework gets updated regularly, ensuring there's always something new to learn.

Till then, pick a topic from this blog and get started on your next great computer science project. You will find projects for professionals, interns, freelancers, as well as final year projects for computer science.

1. Hospital Management System

Type : Application development, Database management, Programming

There is no shortage of computer science project topics out there. But if you are looking for something that's both technically challenging and socially relevant, consider a hospital management system. Such a system would include features like:

Developing an application to manage patient records.
Creating a database to store patient information.
Programming a system to track medical appointments.
designing an algorithm to improve the efficiency of hospital processes.
Investigating the security risks associated with hospital data.
Examining the impact of computerized systems on hospital staff morale.
Evaluating the effectiveness of existing hospital management software.

Source Code: Hospital Management System

2. Weather Forecasting APP

Type: Application development, Web development, Programming

A weather forecasting app is a great idea for final year projects for CSE and can be used to provide users with real-time information about the weather, allowing them to make better decisions about their activities. To develop such an app, you will need to have a strong understanding of computer science concepts such as data structures and algorithms. In addition, you will also need to be familiar with the various APIs that are available for accessing weather data.

Source Code: Weather Forecast App

3. News Feed App

Type: Application designing, Application development, Programming

A news feed app is a great choice for a computer science project. Not only will you learn how to create a user interface, but you'll also gain experience with databases and newsfeed algorithms. To get started, you'll need to gather data from a variety of sources. You can use RSS feeds, APIs, or web scraping techniques to collect this data.

Once you have a dataset, you will need to process it and transform it into a format that can be displayed in your app. This will require some basic Natural Language Processing (NLP) techniques. Finally, you will need to design an algorithm that determines which stories are displayed in the news feed. This can be based on factors such as recency, popularity, or user interests. By working on a news feed app, you will gain valuable skills that are essential for any software developer.

Source Code: News Feed App

4. Optical Character Recognition System (OCR)

Type: Algorithm design, Optical recognition, System Development, Programming

An optical character recognition system, or OCR system, can be a great computer science project topic. OCR systems are used to convert scanned images of text into machine-readable text. This can be a difficult task, as there are often many different fonts and formatting styles that must be taken into account.

However, with the right approach, an OCR system can be an extremely useful tool. Not only can it help to reduce the amount of paper used in an office setting, but it can also help to increase efficiency by allowing users to search through large amounts of text quickly and easily. If you are interested in working on a project that will have a real-world impact, then an OCR system may be the right choice for you.

Source Code: OCR System

5. Library Management System

Type: Database management, System design, System development, Database manipulation, Programming

Library Management Systems can be a great Computer Science project topic because they provide an opportunity to learn about databases and information management. In addition, developing an LMS can be a challenging programming project that requires the use of advanced data structures and algorithms. As a result, working on an LMS can be a great way to develop your skills as a computer programmer.

Source Code: Library Management System

6. Virtual Private Network

Type: Application development, Data security, Networking, Programming

A virtual private network (VPN) is a great project topic for computer science students. VPNs allow users to securely connect to a private network over the internet. By Encrypting data and routing traffic through a VPN server, VPNs can provide a high level of security and privacy. In addition, VPNs can be used to bypass internet censorship and access blocked websites. As a result, VPNs have become increasingly popular in recent years.

There are many different ways to set up a VPN, so computer science students can choose a method that best suits their skills and interests. With a little research, computer science students can create a functional and user-friendly VPN that will be sure to impress their instructors.

Source Code: VPN Project

7. e-Authentication System

Type: Authentication, Information security, System Development, Programming

There are many computer science project ideas out there, but one that is particularly interesting is an e-authentication system. This system would be used to authenticate users and provide them with access to secure online services. The project would involve developing a database of user information, as well as a mechanism for authenticating users.

Depending on the scope of the project, it could also involve developing a user interface and testing the system. This would be a great computer science project for students who are interested in security and authentication. It would also be a good opportunity to learn about databases and web development.

Source Code: e-Authentication System

8. Real-time web search engine

Type: Machine learning, AI, Web annotation, Programming

Real-time web search engines would be a great project for computer science. The idea is to create a search engine that can index and search the web in real time. This would be a major undertaking and would require a team of computer science experts. However, the rewards would be great.

Such a search engine would be immensely useful to everyone who uses the internet. It would also be a major coup for the team that developed it. Therefore, if you are looking for a computer science project that is both challenging and impactful, a real-time web search engine is a great option.

Source Code: Real-time Search Engine

9. Task Management Application

Type: Application design, Application development, Authentication, Database management, Programming

While developing this application, students would learn about database design and development, user interface design, and data structures and algorithms. Ultimately, the goal would be to create an application that is both functional and easy to use.

Source Code: Task Management App

10. Chat App

Type: Application Development, Application designing, Networking, Socket programming, Multi-thread programming

A chat app is a great way to get started with coding and can be one of the ideal mini-project topics for CSE. Not only will you learn how to create a user interface, but you'll also learn how to work with databases and manage user input. Plus, a chat app is a useful tool that you can use in your everyday life. To get started, simply choose a coding language and framework. Then, create a new project in your chosen IDE and start coding! You can begin by designing the UI and then move on to adding features like messaging and file sharing.

Once you have completed the project, you will have a valuable skill that you can use to build other apps or start your own chat app business. And if creating apps intrigues you a lot, you can consider taking a Full Stack Engineer course to polish your skill and attract various hiring companies. With this course, you will gain a deep understanding of how to build, implement, secure and scale programs and access knowledge across the business logic, user interface, and database stacks. Moreover, the professionals may also assist you with your final year project topics for computer engineering.

Source Code: Chatapp

Top Computer Science Project Ideas for Students 2024

Here I’ve compiled a list of the best innovative project ideas for computer science students that you can explore.

1. Face Detection

One popular computer science project is building a face detection system. This involves training a machine learning algorithm to recognize faces in images. Once the algorithm is trained, it can then be used to detect faces in new images. This can be used for a variety of applications, such as security systems and social media apps.

Source Code: Face Detection

2. Online Auction System

Another popular project idea is to build an online auction system. This can be used to sell products or services online. The system would need to include features such as bidding, payments, and shipping. It would also need to be secure so that only authorized users can access the auction site.

Source Code: Online Auction System

3. Evaluation of Academic Performance

This project focuses on developing a system that can evaluate the academic performance of students. The system would need to be able to input data such as grades and test scores. It would then use this data to generate a report card for each student. This project would require knowledge of statistical analysis and machine learning algorithms.

Source Code: Student Performance Analysis

4. Crime Rate Prediction

This project involves building a system that can predict crime rates in different areas. The system would need to input data such as population density, unemployment rate, and average income. It would then use this data to generate predictions for crime rates in different areas. This project would require knowledge of statistical modeling and machine learning algorithms.

Source Code: Crime Prediction App

5. Android Battery Saver System

This project focuses on developing an Android app that can save battery life. The app would need to be able to track the battery usage of other apps on the device. It would then use this information to provide recommendations on how to save battery life. This project would require knowledge of Android development and battery-saving techniques.

Source Code: Android Battery Saver

6. Online eBook Maker

This project focuses on developing a web-based application that can be used to create eBooks. The application would need to allow users to input text, images, and videos into the eBook maker. It would then generate a PDF file that can be downloaded by the user. This project would require knowledge of web development and design principles.

These are just a few ideas for computer science projects that you can try out. If you're stuck for ideas, why not take inspiration from these?

Source Code: Online Ebook Maker

7. Mobile Wallet with Merchant Payment

With a mobile wallet, users can make payments by simply waving their phones in front of a contactless payment terminal. This is not only convenient for consumers but also for merchants, as it reduces the time needed to process payments.

For your project, you could develop a mobile wallet app that includes a merchant payment feature. This would allow users to make payments directly from their mobile wallets to participating merchants. To make things more interesting, you could also add loyalty rewards or coupons that could be redeemed at participating merchants.

Source Code: Mobile wallet

8. Restaurant Booking Website

Another great project idea is to develop a restaurant booking website. This type of website would allow users to search for restaurants by location, cuisine, price range, etc. Once they have found a restaurant they are interested in, they will be able to view available tables and book a reservation.

To make your project stand out, you could focus on making the booking process as smooth and seamless as possible. For example, you could allow users to book tables directly from the restaurant's website or through a third-party platform like OpenTable. You could also integrate with popular calendar apps so that users can easily add their reservations to their calendars.

Source Code: Restaurant Booking System

9. SMS Spam Filtering

With the rise of smartphones, text messaging has become one of the most popular communication channels. However, this popularity has also made it a target for spam messages.

For your project, you could develop an SMS spam filter that uses artificial intelligence techniques to identify and block spam messages. To make things more challenging, you could also develop a system that automatically responds to spam messages with humorous or sarcastic responses.

Source Code: SMS Spam Filtering

10. Library Management System

In this project, you will build a library management system that will allow users to borrow and return books from a virtual library. The system will keep track of which books are currently available and which have been checked out. To complete this project, you will need to design and implement a database system to store information about the books in the library.

11. Twitter Sentiment Analysis

Source Code: Twitter Sentiment Analysis

12. Election Analysis

In this project, you'll collect and analyze data from election campaigns around the world. You can then use the data to answer questions such as "Which candidate is most popular in each country?" or "What issues are most important to voters in each country?" To complete this project, you will need to gather data from multiple sources and analyze it using statistical techniques.

Source Code: Election Analysis

Top Final-Year Project Ideas for Computer Science Students

As a computer science student, you have the unique opportunity to use your skills to create projects that can make a difference in the world. From developing new algorithms to creating apps that solve real-world problems, there are endless possibilities for what you can create.

To get you started, here are the top innovative final-year project ideas for computer science students:

1. Advanced Reliable Real Estate Portal

As the world becomes more digitized, the real estate industry is also starting to move online. However, there are still many challenges with buying and selling property online. For example, it can be difficult to verify the accuracy of listings, and there is often a lack of transparency around fees.

As a computer science student, you could create a more reliable and transparent real estate portal that helps buyers and sellers connect with each other. This could potentially revolutionize the way people buy and sell property, making it simpler and more efficient.

Source Code: Real Estate Portal

2. Image Processing by using Python

Python is a versatile programming language that can be used for a wide range of applications. One area where Python is particularly useful in image processing. You could use Python to develop algorithms that improve the quality of images or that help identify objects in images. This could have applications in areas like security or medicine.

Source Code: Image Processing Using Python

3. Admission Enquiry Chat Bot Project

The process of applying to university can be very daunting, especially for international students. You could create a chatbot that helps prospective students with the admission process by answering their questions and providing information about specific programs. This would make it easier for students to navigate the university application process and increase transparency around admissions requirements.

Source Code: Admission Enquiry Chatbot

4. Android Smart City Travelling Project

With the rise of smart cities, there is an increasing demand for apps that make it easy to get around town. You could develop an Android app that helps users find the fastest route to their destination based on real-time traffic data. This could potentially help reduce traffic congestion in cities and make it easier for people to get where they need to go.

Source Code: Smart City Travelling App

5. Secure Online Auction Portal Project

Auction websites are a popular way to buy and sell items online. However, there are often concerns about security when conducting transactions on these sites. As a computer science student, you could create a secure online auction portal that uses encryption to protect users' personal information. This would give users peace of mind when buying or selling items online and could help increase trust in auction websites.

Source Code: Auction portal

6. Detection of Credit Card Fraud System

With the increase in online shopping and transactions, credit card fraud has become a major problem. With your knowledge of computer science, you can help solve this problem by developing a system that can detect fraudulent activity. This project will require you to analyze data from credit card transactions and look for patterns that indicate fraud. Once you have developed your system, it can be used by businesses to prevent fraudulent transactions from taking place.

Source Code: Credit Card Fraud detection

7. Real Estate Search Based on the Data Mining

The process of buying or selling a home can be a long and complicated one. However, as a computer science student, you can make this process easier by developing a real estate search engine that uses data mining techniques. This project will require you to collect data from various sources (such as MLS listings) and then use analytical methods to identify trends and patterns. This information can then be used to help buyers and sellers find the perfect home.

Source Code: Real Estate Search Based Data Mining

8. Robotic Vehicle Controlled by Using Voice

With the increasing popularity of voice-controlled devices, it's no surprise that there is also interest in developing voice-controlled robotic vehicles. By taking such projects for computer science students, you can help create this technology by developing a system that allows a robotic vehicle to be controlled by voice commands. This project will require you to design and implement software that can interpret voice commands and then convert them into actions that the robotic vehicle can perform.

Source Code: Voice Controlled robot

9. Heart Disease Prediction: Final Year Projects for CSE

Heart disease is one of the leading causes of death worldwide. However, with early detection, many heart diseases can be effectively treated. As a computer science student, you can develop a system that predicts the likelihood of someone developing heart disease based on their medical history and other risk factors. This project will require you to collect data from medical records and then use machine learning algorithms to develop your prediction system.

Source Code: Heart Disease prediction

10. Student Attendance by using Fingerprint Reader

Taking attendance in class is often a time-consuming process, especially in larger classes. As a computer science student, you can develop a fingerprint reader system that automates the attendance-taking process. This project will require you to design and implement software that can read fingerprints and then compare them against a database of students' fingerprints. Once the match is made, the student's name will be added to the attendance list automatically.

Source Code: Attendance with Fingerprint Management

11. Cloud Computing for Rural Banking Project

This project aims to provide an efficient and secure banking system for rural areas using cloud computing technology. The project includes the development of a web-based application that will allow users to access their accounts and perform transactions online. The application will be hosted on a remote server and will be accessible from any location with an internet connection. The project will also include the development of a mobile app for users to access their accounts on their smartphones.

Source Code: Banking System

12. Opinion Mining for Comment Sentiment Analysis

This project involves developing a system that can automatically analyze the sentiment of comments made on online platforms such as news articles, blog posts, and social media posts. The system will use natural language processing techniques to identify the sentiment of each comment and generate a report accordingly. This project can be used to monitor public opinion about various topics and issues.

Source Code: Opinion Mining Sentiment Analysis

13. Web Mining for Suspicious Keyword Prominence

This project involves developing a system that can crawl through websites and identify keywords that are being used excessively or in a suspicious manner. The system will flag these keywords and notify the administrator so that they can further investigate the matter. This project can be used to detect spam websites or websites that are engaged in black hat SEO practices.

Source Code: Web Mining

14. Movies recommendations by using Machine Learning

This project involves developing a system that can recommend movies to users based on their previous watching history. The system will use machine learning algorithms to learn the user's preferences and make recommendations accordingly. This project can be used to create a personalized movie recommendation system for each user.

Source Code: Movie Recommender System

15. Online Live Courier Tracking and Delivery System Project

This project aims to develop a system that can track the live location of courier packages and provide real-time updates to the sender and receiver about the status of the delivery. The system will use GPS technology to track the location of courier packages and update the status in the database accordingly. This information will then be made available to users through a web-based or mobile application.

Source Code: Courier Tracking & Delivery System

How to Choose a Project Topic in Computer Science?

Picking a project topic in computer science can feel like a challenge. However, I've found a few steps that can make the process a bit easier.

How to Choose a Project Topics In Computer Science

1. Define your goals

The first step is to define your goals for the project. What do you hope to achieve by the end of it? Do you want to develop a new skill or build on existing ones? Do you want to create something that will be used by others? Once you have defined your goals, you can narrow down your focus and start thinking about potential topics.

2. Do your research and Get inspired by real-world problems

Once you have an idea of what you want to do, it's time to start researching potential topics. Talk to your supervisor, read through course materials, look at past projects, and search online for ideas. When doing your research, it is important to keep your goals in mind so that you can identify topics that will help you achieve them.

3. Consider the feasibility

Once you have shortlisted some potential topics, it's time to consider feasibility. Can the topic be completed within the timeframe and resources available? Is there enough information available on the topic? Are there any ethical considerations? These are all important factors to take into account when choosing a topic.

4. Make a decision

After considering all of the above factors, it's time to make a decision and choose a topic for your project. Don't worry if you don't know exactly what you want to do at this stage, as your supervisor will be able to help guide you in the right direction. The most important thing is that you choose a topic that interests you and that you feel confident about tackling it.

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Conclusion

If you are a student looking for a computer science project topic or an employee searching for interesting ideas to improve your skills, I hope this article has given you some helpful direction. I have provided a variety of project topics in different areas of computer science so that you can find one that sparks your interest and challenges you to learn new things.

I also want to encourage you to explore the resources available online and through your own community to continue expanding your knowledge in this rapidly changing field. On that note, KnowledgeHut’s best online course for Web Development can help you with the different aspects of computer science. With experienced professionals as your instructors, you will be able to gain knowledge and expertise that will benefit you both professionally and academically. Why wait? Learn something new today!

Frequently Asked Questions (FAQs)

Final year projects for computer science are important because they allow students to apply the knowledge and skills that they have acquired over the course of their studies. By working on a real-world problem or challenge, students have the opportunity to develop practical expertise and learn how to work effectively as part of a team.

Yes, final year projects can be very important for landing a job after graduation. Many employers use final-year projects as a way to assess a candidate's skills and abilities, and they may even use it as a tiebreaker when reviewing multiple candidates who are equally qualified. As such, students should take their final year projects seriously and put forth their best effort.

Final-year projects also provide students with valuable experience that can help them in their future careers. If you select the best project topics for computer science students and work hard, you may be successful in your final year project.

Failing in a final-year project can be discouraging, but it is not the end of the world. One way to try and ensure passing is by taking mini-project topics for computer science. This will help show that you have the ability to complete projects and pass with flying colors. Additionally, try and get feedback from your professors on what areas you need to improve in.

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Research Opportunities

Undergraduate research in computer science.

For specific information on undergraduate research opportunities in Computer Science visit https://csadvising.seas.harvard.edu/research/ .

General Information about Undergraduate Research

Opportunities for undergraduates to conduct research in engineering, the applied sciences, and in related fields abound at Harvard. As part of your coursework, or perhaps as part of individual research opportunities working with professors, you will have the chance to take part in or participate in some extraordinary projects covering topics ranging from bioengineering to cryptography to environmental engineering.

Our dedicated undergraduate research facilities and Active Learning Labs also provide opportunities for students to engage in hands-on learning. We encourage undergraduates from all relevant concentrations to tackle projects during the academic year and/or over the summer.

Keep in mind, many students also pursue summer research at private companies and labs as well as at government institutions like the National Institutes of Health.

If you have any questions, please contact or stop by the Office of Academic Programs, located in the Science and Engineering Complex, Room 1.101, in Allston.

Research FAQs

The SEAS website has a wealth of information on the variety of cross-disciplinary research taking place at SEAS. You can view the concentrations available at SEAS here , as well as the research areas that faculty in these concentrations participate in. Note that many research areas span multiple disciplines; participating in undergraduate research is an excellent way to expand what you learn beyond the content of the courses in your concentration!

To view which specific faculty conduct research in each area, check out the All Research Areas section of the website. You can also find a helpful visualization tool to show you the research interests of all the faculty at SEAS, or you can filter the faculty directory by specific research interests. Many faculty’s directory entry will have a link to their lab’s website, where you can explore the various research projects going on in their lab.

The Centers & Initiatives page shows the many Harvard research centers that SEAS faculty are members of (some based at SEAS, some based in other departments at Harvard).

Beyond the website, there are plenty of research seminars and colloquia happening all year long that you can attend to help you figure out what exactly you are interested in. Keep an eye on the calendar at https://events.seas.harvard.edu !

There are several events that are designed specifically for helping undergraduate students get involved with research at SEAS, such as the Undergraduate Research Open House and Research Lightning Talks . This event runs every fall in early November and is a great opportunity to talk to representatives from research labs all over SEAS. You can find recordings from last year’s Open House on the SEAS Undergraduate Research Canvas site .

Most of our faculty have indicated that curiosity, professionalism, commitment and an open mind are paramount. Good communication skills, in particular those that align with being professional are critical. These skills include communicating early with your mentor if you are going to be late to or miss a meeting, or reaching out for help if you are struggling to figure something out. Good writing skills and math (calculus in particular) are usually helpful, and if you have programming experience that may be a plus for many groups. So try to take your math and programming courses early (first year) including at least one introductory concentration class, as those would also add to your repertoire of useful skills.

Adapted from the Life Sciences Research FAQs

Start by introducing yourself and the purpose of your inquiry (e.g. you’d like to speak about summer research opportunities in their lab). Next, mention specific aspects of their research and state why they interest you (this requires some background research on your part). Your introduction will be stronger if you convey not only some knowledge of the lab’s scientific goals, but also a genuine interest in their research area and technical approaches.

In the next paragraph tell them about yourself, what your goals are and why you want to do research with their group. Describe previous research experience (if you have any). Previous experience is, of course, not required for joining many research groups, but it can be helpful. Many undergraduates have not had much if any previous experience; professors are looking for students who are highly motivated to learn, curious and dependable.

Finally, give a timeline of your expected start date, how many hours per week you can devote during the academic term, as well as your summer plans.

Most faculty will respond to your email if it is clear that you are genuinely interested in their research and have not simply sent out a generic email. If you don’t receive a response within 7-10 days, don’t be afraid to follow up with another email. Faculty are often busy and receive a lot of emails, so be patient.

There are several ways that undergraduate research can be funded at SEAS. The Program for Research in Science and Engineering ( PRISE ) is a 10-week summer program that provides housing in addition to a stipend for summer research. The Harvard College Research Program ( HCRP ) is available during the academic year as well as the summer. The Harvard University Center for the Environment ( HUCE ) has a summer undergraduate research program. The Harvard College Office of Undergraduate Research and Fellowships ( URAF ) has more information on these, as well as many other programs.

Students that were granted Federal Work Study as part of their financial aid package can use their Work Study award to conduct undergraduate research as well (research positions should note that they are work-study eligible to utilize this funding source).

Research labs may have funding available to pay students directly, though we encourage you to seek out one of the many funding options available above first.

Yes! Some students choose to do research for course credit instead of for a stipend. To do so for a SEAS concentrations, students must enroll in one of the courses below and submit the relevant Project Application Form on the Course’s Canvas Page:

Applied Mathematics 91r (Supervised Reading and Research)
Computer Science 91r (Supervised Reading and Research)
Engineering Sciences 91r (Supervised Reading and Research)

In general, you should expect to spend a minimum of one semester or one summer working on a project. There are many benefits to spending a longer period of time dedicated to a project. It’s important to have a conversation early with your research PI (“Principal Investigator”, the faculty who runs your research lab or program) to discuss the intended timeline of the first phase of your project, and there will be many additional opportunities to discuss how it could be extended beyond that.

For students who are satisfied with their research experience, remaining in one lab for the duration of their undergraduate careers can have significant benefits. Students who spend two or three years in the same lab often find that they have become fully integrated members of the research group. In addition, the continuity of spending several years in one lab group often allows students to develop a high level of technical expertise that permits them to work on more sophisticated projects and perhaps produce more significant results, which can also lead to a very successful senior thesis or capstone design project.

However, there is not an obligation to commit to a single lab over your time at Harvard, and there are many reasons you may consider a change:

your academic interests or concentration may have changed and thus the lab project is no longer appropriate
you would like to study abroad (note that there is no additional cost in tuition for the term-time study abroad and Harvard has many fellowships for summer study abroad programs)
your mentor may have moved on and there is no one in the lab to direct your project (it is not unusual for a postdoctoral fellow who is co-mentoring student to move as they secure a faculty position elsewhere)
the project may not be working and the lab hasn’t offered an alternative
or there may be personal reasons for leaving. It is acceptable to move on

If you do encounter difficulties, but you strongly prefer to remain in the lab, get help. Talk to your PI or research mentor, your faculty advisor or concentration advisor, or reach out to [email protected] for advice. The PI may not be aware of the problem and bringing it to their attention may be all that is necessary to resolve it.

Accepting an undergraduate into a research group and providing training for them is a very resource-intensive proposition for a lab, both in terms of the time commitment required from the lab mentors as well as the cost of laboratory supplies, reagents, computational time, etc. It is incumbent upon students to recognize and respect this investment.

One way for you to acknowledge the lab’s investment is to show that you appreciate the time that your mentors set aside from their own experiments to teach you. For example, try to be meticulous about letting your mentor know well in advance when you are unable to come to the lab as scheduled, or if you are having a hard time making progress.
On the other hand, showing up in the lab at a time that is not on your regular schedule and expecting that your mentor will be available to work with you is unrealistic because they may be in the middle of an experiment that cannot be interrupted for several hours.
In addition to adhering to your lab schedule, show you respect the time that your mentor is devoting to you by putting forth a sincere effort when you are in the lab. This includes turning off your phone, ignoring text messages, avoiding surfing the web and chatting with your friends in the lab etc. You will derive more benefit from a good relationship with your lab both in terms of your achievements in research and future interactions with the PI if you demonstrate a sincere commitment to them.
There will be “crunch” times, maybe even whole weeks, when you will be unable to work in the lab as many hours as you normally would because of midterms, finals, paper deadlines, illness or school vacations. This is fine and not unusual for students, but remember to let your mentor know in advance when you anticipate absences. Disappearing from the lab for days without communicating with your mentor is not acceptable. Your lab mentor and PI are much more likely to be understanding about schedule changes if you keep the lines of communication open but they may be less charitable if you simply disappear for days or weeks at a time. From our conversations with students, we have learned that maintaining good communication and a strong relationship with the lab mentor and/or PI correlates well with an undergraduate’s satisfaction and success in the laboratory.
Perhaps the best way for you to demonstrate your appreciation of the lab’s commitment is to approach your project with genuine interest and intellectual curiosity. Regardless of how limited your time in the lab may be, especially for first-years and sophomores, it is crucial to convey a sincere sense of engagement with your project and the lab’s research goals. You want to avoid giving the impression that you are there merely to fulfill a degree requirement or as a prerequisite for a post-graduate program.

There are lots of ways to open a conversation around how to get involved with research.

For pre-concentrators: Talk to a student who has done research. The Peer Concentration Advisor (PCA) teams for Applied Math , Computer Science and Engineering mention research in their bios and would love to talk about their experience. Each PCA team has a link to Find My PCA which allows you to be matched with a PCA based on an interest area such as research.
For SEAS concentrators: Start a conversation with your ADUS, DUS, or faculty advisor about faculty that you are interested in working with. If you don’t have a list already, start with faculty whose courses you have taken or faculty in your concentration area. You may also find it helpful to talk with graduate student TFs in your courses about the work they are doing, as well as folks in the Active Learning Labs, as they have supported many students working on research and final thesis projects.
For all students: Attend a SEAS Research Open House event to be connected with lab representatives that are either graduate students, postdocs, researchers or the PI for the labs. If you can’t attend the event, contact information is also listed on the Undergraduate Research Canvas page for follow-up in the month after the event is hosted.

For any student who feels like they need more support to start the process, please reach out to [email protected] so someone from the SEAS Taskforce for Undergraduate Research can help you explore existing resources on the Undergraduate Research Canvas page . We especially encourage first-generation and students from underrepresented backgrounds to reach out if you have any questions.

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Research project ideas for Computer Science students

Sometimes Computer Science students struggle to find a final year research topic. In this post, you will find some ideas that can help you define a topic you can develop for your final year research project.

Once you choose your project, it is time to write your research proposal. I’ll leave some links at the end of this post that will guide you on how to do it.

1. mobile app for class notes, 2. graphic simulator of programming structures and basic algorithms., 3. augmented reality app to support the learning of oop concepts., 4. augmented reality app to translate uml to a code, 5. moodle reports dashboard.

This app won’t be just another note-taking app. In this case, you can build it with specific requirements to facilitate the students learning process.

Some of the requirements can be:

Instructors can load a course to the app. This will include the course outline and notes.
Students can subscribe to a certain course. Then, they will have access to all the information uploaded by the instructor.
Students can take their own notes and decide whether to share them or not.
The notes should be easily discovered and grouped by topic and/or unit.

Main advantage: Students will be able to use the accumulated experience (by instructors and other students) in a certain subject.

This topic will result in a progressive web application that can show, graphically, what exactly is happening while the computer executes the following:

Conditionals
Basic algorithms: counting, summing, maximum
Call to methods

It is well accepted that graphic representations help students to learn better. Also, there is one skill that is especially difficult for students named tracing.

Tracing is about finding out what will be the output of a given code. Understanding how the basic algorithms and programming structures work graphically will help students to grasp this skill.

This will be a cool app the students will just love.

The requirements will be the following:

– Once you point the camera to an object in the real world, the app first should identify the object.

– The app will give options to show attributes of the object (color, size, etc.)

– Show available actions to the object.

– Be able to execute some of the actions.

– Show a UML class diagram for the class, showing attributes and methods.

The requirements will be as follows:

– Point the camera to a UML diagram.

– Show options for different programming languages.

– Show the code of the class in a specific programming language.

– Output the code to a file.

– Give options to save the file: upload to an FTP server, save locally, upload to a git repository, cloud integration, etc.

Moodle is a well-known Learning Management System (LMS). It includes a list of useful reports, although some of them do not have the best presentation design.

This application can be developed as Moodle plugin. In this link, you can find a tutorial on how to develop a plugin for Moodle.

Some requirements that can be implemented are the following:

– Dashboard with user-defined Key Performance Indicators (KPI).

– Choose what type of graphs to show on the dashboard.

– Options to show any of the reports that Moodle already provides integrated on the dashboard. See the picture below.

– Options to track the performance of students with average marks within a certain range. This can help the lecturer to give special attention to students with difficulties.

– Additional reports of interest. To define which reports, the researcher should conduct interviews/questionnaires with lecturers and HoDs to find out what type of report will be useful for each of them. From these artefacts, the researcher will gain insights on how to better build the dashboard and include initial KPIs.

And that’s all for now.

I’ll keep updating this list regularly. So, if these ones don’t fit your preferences, come back again in a while. You are most welcome to leave a comment below.

How to write the background of the study for a research proposal?
How to write a problem statement for a research proposal?
How to write research objectives for a research proposal?
How to write the research methodology?
How to write a literature review?
How to write your research proposal?
How to write an abstract for your research paper, proposal, or dissertation?

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2020-2021 SURE Research Projects in CSE

This page lists summer research opportunities in CSE that are available through the SURE Program. To learn more or apply, visit: https://sure.engin.umich.edu/ .

Please carefully consider each of the following projects, listed below, before applying to the SURE Program.
You must indicate your top three project choices on your SURE application, in order of preference, using the associated CSE project number.
Questions regarding specific projects can be directed to the listed faculty mentor.

Project descriptions

CSE Project #1: Natural Language Processing for Understanding Media Bias and Fake News Faculty Mentor: Lu Wang [wangluxy @ umich.edu] Prerequisites: EECS 445 (Machine Learning), probability and statistics, experience with natural language processing problems, proficient in Python. Description: News media play a vast role not just in supplying information, but in selecting, crafting, and biasing that information to achieve both nonpartisan and partisan goals. We aim to automate media bias detection from news articles, and quantify and further highlight biased content in order to promote the transparency of news production as well as enhance readers’ awareness of media bias. This project will explore and design natural language processing and machine learning algorithms to detect media bias. Specifically, we will work on developing information extraction systems, e.g., important entities and narrative structure will be extracted automatically from news articles. The developed tools will also be used for understanding fake news. Expected research delivery mode: Hybrid

CSE Project #2: Computational Strategic Reasoning Faculty Mentor: Michael Wellman [wellman @ umich.edu] Prerequisites: Programming ability; interest/background in finance, economics, game theory, and/or statistics (helpful though not required). Description: The Strategic Reasoning Group (strategicreasoning.org) develops computational tools to support reasoning about complex strategic environments. Recent applications include scenarios arising in finance and cyber-security. We employ techniques from agent-based modeling, game theory, and machine learning. Expected research delivery mode: Too soon to say

CSE Project #3: Taming the Performance Bottlenecks of Modern Web Applications Faculty Mentor: Baris Kasikci [barisk @ umich.edu] Prerequisites: EECS 482 Description: Modern data-center applications suffer significant slow-down due to large number instruction cache-misses. To reduce such cache-misses, recent studies have advocated the introduction of a new code prefetch instruction. While warehouse-scale processors do not support this feature yet, some mobile processors already support this code prefetch instruction. In this study, we will design a compiler backend to inject code prefetch instruction both statically and based on profile data in order to evaluate several data-center applications on mobile such processors. Expected research delivery mode: Too soon to say

CSE Project #4: Web automation using program synthesis Faculty Mentor: Xinyu Wang [xwangsd @ umich.edu] Prerequisites: EECS 485 or equivalent, and familiarity with HTML/DOM/JS Description: Many computer end-users often need to perform tasks that involve the web, such as filling online forms, extracting data, which are repetitive and tedious in nature. On the other hand, there are existing programming languages that can be used to automate these tasks. However, writing web automation scripts is far beyond the capability of end-users who have very little programming background. In this project, we aim to help users automate web-related programming tasks using program synthesis. Expected research delivery mode: Too soon to say

CSE Project #5: Interactive program synthesis Faculty Mentor: Xinyu Wang [xwangsd @ umich.edu] Prerequisites: Familiarity with one programming language. Description: Program synthesis aims to automatically generate programs from user intent expressed in some high-level format (such as input-output examples). It has found a lot of applications, for instance, in data science, software development, etc. While there has been a lot of algorithmic advancements in program synthesis techniques, it is still unclear what is the best way for synthesizers to interact with users. In this project, we will explore how to design interactive program synthesis algorithms as well as good user interfaces for these techniques. Expected research delivery mode: Too soon to say

CSE Project #6: Superoptimization using program synthesis Faculty Mentor: Xinyu Wang [xwangsd @ umich.edu] Prerequisites: Compilers, strong programming and engineering background. Description: The goal of superoptimization is to automatically derive compiler optimizations. It automatically searches among a space of optimizations and apply those that can be applied for the input program. The advantage of superoptimization is that it can dramatically reduce human effort and at the same time potentially generate better optimizations. In this project, we will look at how to use program synthesis and program analysis to automatically derive better optimizations more efficiently, compared to prior superoptimization techniques. Expected research delivery mode: Too soon to say

CSE Project #7: Censored Planet: A Global Observatory for Internet Censorship Faculty Mentor: Roya Ensafi [ensafi @ umich.edu] Prerequisites: EECS 388 and EECS 482 Description: The Internet Freedom community’s understanding of the current state and global scope of censorship remains limited: most work to-date has focused on the practices of particular networks and countries, or on the reachability of small sets of online services and from a small number of volunteers. Creating a global, data-driven view of censorship is a challenging proposition, since censorship practices are intentionally opaque, and there are a host of mechanisms and locations where disruptions can occur. Moreover, the behavior of the network can vary depending on who is requesting content from which location.

Fall 2018, Prof. Ensafi launched a pilot of Censored Planet, an online observatory for Internet censorship that applies all of next-generation measurement techniques in order to rapidly, continuously, and globally track online censorship. Data from the pilot has already been used by dozens of organizations, and it has helped provide insight into important events like Saudi Arabia’s reaction to the death of Jamal Khashoggi, the proliferation of DPI-based censorship products, and recent HTTPS interception attacks sponsored by the government of Kazakhstan.

We seek to extend and fully operationalize Censored Planet and make data from next-generation remote censorship measurements more useful to the entire Internet Freedom community. We plan to mature the project from a pilot to a production system with significant improvements in performance, stability, usability, and code quality; implement an API and new “rapid focus” capabilities to agily respond to world events; and develop aggregation and analysis tools to automatically extract useful insights from that data. We will also cultivate a community of civil society organizations and tool developers to ensure the data best serves real-world needs.

By helping create a more complete picture of global censorship than ever before, Censored Planet will allow researchers and policymakers to closely monitor for deployment of censorship technologies, track policy changes in censoring nations, and better understand the targets of interference. Making opaque censorship practices more transparent at a global scale will help counter the proliferation of these growing restrictions to online freedom. Expected research delivery mode: Remote

CSE Project #8: Supporting K-5 Children Learning While Using the Collabrify Roadmap Platform Faculty Mentor: Elliot Soloway [soloway @ umich.edu] Prerequisites: Competency in Javascript, databases, interfaces. Description: The Center for Digital Curricula in the College of Engineering provides deeply-digital curricula, standards-aligned to K-5 classrooms – free. During the fall 2020 semester, over 5,000 K-5 students are using the Center’s curricula on a daily basis. Students use the Collabrify Roadmap Platform to enact the digital curricula. Teachers and students request changes to the Platform; and researchers see opportunities to make the Platform still more effective. During the summer, then, the Center is seeking two ugrads to work on projects to implement the requested changes to the Platform. Join us in helping children to learn more effectively! Expected research delivery mode: Hybrid

CSE Project #9: Computer Vision for Physical and Functional Understanding Faculty Mentor: David Fouhey [fouhey @ umich.edu] Prerequisites: Good grades in EECS 442 OR EECS 445. Description: The lab is broadly focused on building 3D representations of the world and understanding human/object interaction. Potential projects include learning about: navigating environments, object articulations, commonsense physical properties of objects, and hand grasps. Please look at:http://web.eecs.umich.edu/~fouhey/ for a sense of what projects we’ve done in the past. We will find a specific project based on mutual interest and particular abilities (e.g., stronger systems programming abilities, experience with graphics, etc.). Students looking for a longer term project continuing during the school year are strongly encouraged to apply. Expected research delivery mode: Too soon to say

CSE Project #10: Does Wealth Matter? Learning Generative Models with Prediction Markets Faculty Mentor: Mithun Chakraborty and Sindhu Kutty [skutty @ umich.edu] Prerequisites: EECS 445 and STATS 412 (or equivalents) preferred. Description: As recent events have highlighted, polling can be messy, misleading and prone to misinterpretation. Markets have the advantage over polls in having built-in financial incentives and timely responses, and have been empirically observed to outperform alternative forecasting tools such as polls. However, when traders have varying degrees of wealth, are markets egalitarian? Moreover, how precise are they and what factors impact their precision? We will answer these questions in the context of Prediction Markets by tying market prices to learning a generative model of the outcome space. We will also explore other connections between convergence in Machine Learning algorithms (especially Bayesian processes) and equilibria in these markets.

Prediction markets (e.g. Iowa Electronic Markets, PredictIt, etc.) are a type of financial market the purpose of which is to elicit the personal beliefs of traders about a future uncertain event and aggregate these beliefs into the market price. In this project, students will implement and execute a set of experiments on the interaction of a new prediction market design with simulated trading agents having diverse risk attitudes and help address the above research questions in different environments in a systematic manner. An understanding of connections to Machine Learning algorithms would be illustrative for gauging the accuracy, and hence reliability, of Prediction Markets and can, in turn, inform innovations in their design. The learning outcome for students will be hands-on experience in interdisciplinary research with connections to Machine Learning and Computational Economics. Expected research delivery mode: Remote

CSE Project #11: Hazel Notebooks: Building a Better Jupyter Faculty Mentor: Cyrus Omar [comar @ umich.edu] Prerequisites: EECS 490 or equivalent is preferred, but not required. Description: The popular Jupyter lab notebook environment is powerful, but it has a problem: results stored in a notebook are not reproducible, because the user can execute cells out of order. In our group, we are developing a new live functional programming environment called Hazel (hazel.org). Right now, Hazel does not support multiple program cells. This project will turn Hazel into a next-generation version of Jupyter by adding support for notebooks with multiple cells, with dependencies between them. We will solve the reproducibility problem by developing a mechanism conjectured in a recent paper in our group: fill-and-resume. Expected research delivery mode: Too soon to say

CSE Project #12: Hazel: A Live Functional Programming Environment Faculty Mentor: Cyrus Omar [comar @ umich.edu] Prerequisites: EECS 490 or equivalent is preferred, but not required. Description: Hazel (hazel.org) is a live functional programming environment that is able to typecheck, transform and even execute incomplete programs, i.e. programs with holes. There are a number of projects available within the Hazel project for a student interested in research into programming languages. Expected research delivery mode: Too soon to say

CSE Project #13: Ubiquitous Health Sensing Faculty Mentor: Alanson Sample [apsample @ umich.edu] Prerequisites: Experience with embedded systems, computer vision, or machine learning Description: Effective means of unobtrusive and continuous monitoring of one’s health could transform how we detect and treat illnesses. This project aims to create a long-range health monitoring system that can passively measure an individual’s vital signs and daily activities from a distance of up to three meters. Building off of novel sensing techniques developed in the Interactive Sensing and Computing Lab, SURE students will work with faculty and graduate student mentors to create a fully working end-to-end system, utilizing embedded systems, computer vision, and machine learning. Expected research delivery mode: Hybrid

CSE Project #14: The Internet of Everything: Bringing everyday objects into the digital world with RFID tags Faculty Mentor: Alanson Sample [apsample @ umich.edu] Prerequisites: Strong programming skills. Description: RFID tags are battery-free, paper-thin stickers that can communicate with RFID readers from +8 meters of distance. These tags offer a minimalistic means of instrumenting everyday objects. By monitoring changes in the low-level communication channel parameters between the tag and reader, it is possible to turn an RFID tag into an ultra-low-cost, battery-free sensor. Applications include in-home activity inferencing, interactive physical objects, and health and wellness monitoring. Expected research delivery mode: Too soon to say

CSE Project #15: Computer Vision for Physical and Functional Understanding Faculty Mentor: Alanson Sample [apsample @ umich.edu] Prerequisites: Preferred EECS 311 or EECS 373. Description: This project encompasses a number of efforts at developing energy harvesting, battery free sensing systems that can be easily embedded into everyday objects and thus allowing for near perpetual operation. Topics include ambient energy harvesting techniques, platform architecture and power management, and debugging tools that deal with intermittent power. Expected research delivery mode: Too soon to say

CSE Project #16: Adversarial Human-AI Interactions in the On-Demand Economy Faculty Mentor: Nikola Banovic [nbanovic @ umich.edu] Prerequisites: Familiarity with programming (i.e., Python), interest in applied machine learning and human-computer interaction. Description: AI has started to transform the nature of work in many sectors of the economy. One of the most tangible transformations has been in the on-demand economy, for services such as grocery delivery, ride-hailing, and other last-mile services, where its advances have allowed a shift towards greater efficiency, through the use of AI-mediated platforms. On-demand work, with its promises of flexibility, independence and entrepreneurship is also an attractive option for individuals seeking a low-barrier entry into employment and economic opportunities. However, several recent debates around the employment status of workers with services such as Uber, Lyft and Instacart have shined a light on the adversarial relationships between workers and platforms, and the negative effects of opaque algorithms on workers’ well-being. In this project, we seek to design computational methods to audit these opaque platforms to uncover sources of adversarial human-AI interactions that may be potentially harmful to on-demand workers. Our goal is to understand the design of algorithmic platforms that enhance worker well-being and their access to economic opportunities. Expected research delivery mode: Remote

CSE Project #17: Novel Architectures to Compute with Graphs Faculty Mentor: Valeria Bertacco [valeria @ umich.edu] Prerequisites: EECS 281, EECS 370. Recommended: C++, scripting. Description: More and more applications rely on graphs as the underlying data structure: from social networks, to internet’s web connections, to geo maps, to ML algorithms and even consumers’ product preferences. The performance of these algorithms is often limited by the latency of accessing vertices in memory, whose access present poor spatial locality. The goal of this project is to boost the performance of graph-based algorithms by developing hardware and software solutions to this end: we plan to work on the data layout, on ad-hoc data structures and on designing dedicated hardware acceleration blocks. We hope to boost the performance of graph traversals by 3-5x. Expected research delivery mode: Too soon to say

CSE Project #18: From High-Level Language to Hardware — Without the Hardware Design Faculty Mentor: Valeria Bertacco [valeria @ umich.edu] Prerequisites: EECS 281. Recommended: C++, scripting. Description: This project explores a new hardware design flow, where the starting point is an application specified in a domain-specific language (more specialized than C) like Halide or GraphIt, and the endpoint is a hardware system equipped with specialized hardware accelerators, so to execute the application much faster than it would be possible in software. To reach the endpoint, we will work on the back-end of the compiler, so to target the primitives available in the hardware accelerators. Expected research delivery mode: Too soon to say

CSE Project #19: Computing on Encrypted Data Faculty Mentor: Valeria Bertacco [valeria @ umich.edu] Prerequisites: EECS 280, EECS 370. Recommended: C++, scripting. Description: In the age of big data, privacy is a key concern in sharing data. Unfortunately, the field of security is riddled with stories of security attacks…even to the most secure enclaves. The solution we want to investigate with this project uses encryption technology to encrypt data locally, transfer it to the cloud for any required computation, and receive encrypted results back. The enhanced cloud system performs the computation directly on the encrypted data without an access key — it never accesses the plaintext data nor can it decrypt the sensitive data. Only the end device, can decrypt the result and store it locally. Expected research delivery mode: Too soon to say

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Top 20 Computer Science Research and Passion Project Ideas for High School Students

By Logan Pearce

PhD candidate in Social Psychology at Princeton University

13 minute read

Computer Science (CS) is fast becoming one of the most popular academic majors in US colleges.

At Stanford University, CS has risen to take the number 1 spot as the most popular undergraduate major, followed by economics, engineering, human biology, and my major, Symbolic Systems . If you’re a high school student itching to try your hand at an independent project in computer science, try out one of these 20 computer science project ideas that you can pursue in the comfort of your own home!

5 Computer Science Projects in Game Design

Games are a really fun way for high schoolers to get started with computer science. You get to develop your skills as a computer scientist while having fun with something you made! Here are a few ideas of games that you can make:

1. Number guessing game

If you only have a little bit of experience with computer science, try implementing this game before moving on to more complex projects. You’ll program the computer to think of a number between 1 and 10. The player guesses what number the computer is thinking of, and the player has to keep guessing until they get it right. You can also make the reverse version of the game - the player thinks of a number and the computer guesses what the player is thinking.

Even though the basic idea of this game is simple, there are lots of fun and complex variations that you can add. For example, when the player is guessing the number, you can write code to tell the player if the number they guessed is higher or lower than what the computer is thinking and/or alert the player if they guess a number that they already guessed before. When the computer is guessing the number, you can write code to detect if the player changed their number and/or guess the number faster by asking the player if their number is higher or lower than what the computer guessed.

Idea by computer science mentor Logan (me!)

2. Choose-your-own-adventure story

In a choose-your-own-adventure game, players are presented with situations like: You are in a dark room and you hear a knock at the door, what do you want to do?: 1) Open the door or 2) Explore the room. Based on what the player chooses, the story goes in different directions! In this project, you will have the full creative freedom to build a choose-your-own-adventure game with as many twists and turns as your heart desires. You’ll learn the basic principles of programming, such as how loops and functions work.

Idea by computer science mentor Carina

3. Tic tac toe

In this project, you’ll create a board that players can use to play tic tac toe. Players will alternate placing their marker (i.e., “X” or “O”) on the board. After each player moves, the computer will check to see if the player won the game.

Let’s face it, basic tic tac toe is a little boring, so time to add some excitement by implementing more complex versions! Adapt your game board so that players can play odds/evens tic tac toe and odds/evens tic tac toe with parity.

Check out the details of those tic-tac-toe variations here

In the beginner version of this project, players won’t be able to click on the game board. Instead, you’ll use letters to mark each letter on the board. Thus, each tile will be marked by a letter from a - i. Each player will type the letter of the tile that they want to put their marker on.

In the intermediate version of the project, you’ll create a Graphical User Interface (GUI) so that players can click on the board.

/Intermediate

Idea by computer science mentor Logan

4. Educational video game

There are many ways to teach nowadays, and more often than not, games are one of the best facets to encourage learning that is both fun and constructive. From infancy through adulthood, games have been used to share information and teach fundamental concepts. You can make a math game, a typing game, or anything else that you want!

Idea by computer science mentor Hannah

5. 2D or 3D game

For students who are interested in game development and have some prior experience with computer science, designing your own game is a great passion project! You get to conceptualize, design, and implement your very own game. You can decide to make a 2D game like Galaga or Donkey Kong, a 3D game where you fight monsters, or any other kind of game.

Idea by computer science mentor Sahil

Create a CompSci research project tailored to YOU!

Polygence pairs you with an expert mentor in your area of passion. Together, you explore the area of Computer Science that ignites your mind to create a high quality research project that is uniquely your own. We also offer options to explore multiple topics, or to showcase your final product!

3 Computer Science Projects in Design

1. there’s an app for that.

If you have been coding for a while and have an idea of just what the world needs next in the app world, this might be the perfect project for you! Learn to design, code, and create an app from start to finish and share it with your friends and family. If you want, you can even publish it on the app store (for a small fee) and see what kind of traction you get! You can use MIT's App Inventor or Code.org's App Lab as resources as you embark on your app development journey.

Idea by computer science mentor Abigail

2. Make your own website

In this project, you will learn the fundamentals of web development by creating your own website. You will deploy this website to the world wide web, and create several different pages with content of your choice. Will you make a professional page with your resume and bio? A site with games for your friends? Maybe a blog or collection of articles?

Idea by computer science mentor Sam

3. Design research and development

Design is rooted in problem-solving and creating elegant solutions. You will identify an issue, do social research, and analyze data. Ultimately, you will develop a design solution that can be integrated into daily life. Projects could include designing an app, website, product, or virtually anything that needs fixing. This project is different from the previous two in that you will investigate your issue and design a solution without having a set end goal in mind. Everything in our lives is designed, so let's design it better!

Idea by computer science mentor Amira

5 Computer Science Projects in Data Analysis

1. combining datasets to extract insights.

Data comes in many different places and is often most powerful when combined. This project is simple and open-ended. Find two or more datasets regarding some topic of your choice that you think might add additional insight when taken together. Your goal will be to join those datasets together and find out something cool! Depending on your ambition/comfort with Javascript, HTML, and CSS, you can even try creating a basic dashboard that allows other people to find out information about your topic.

For instance, the mentor who proposed this project once created a dashboard that combined housing data from Zillow, US Census data, and business information from Yelp to create an app that would help prospective movers find areas that fit their lifestyle on a certain budget. This project will likely make heavy use of SQL, as well as Python for preprocessing.

Idea by computer science mentor Daniel

2. A comprehensive analysis of passwords

You probably have seen that many websites have certain password requirements like, "Must contain one capital letter, a symbol, a number, etc.” Using some form of rule induction, pattern recognition, or machine learning, as well as one of the many datasets of password leaks available online, find the patterns in how people choose passwords, and how those can be protected. For instance, if people are using a capital letter, does it often appear at the beginning of the password? How often are passwords just English words, as opposed to a random set of characters?

Idea by computer science mentor Hirsh

3. Understanding mental health through social media

Social media can be a lens into the lives and well-being of individuals. Using the social media platform of interest, you can study how useful posts, interactions, and other information are in predicting and understanding mental health and mental illness. You will use statistical and machine learning tools to search for relationships between social media and mental health. You can also survey people who use social media to complement your analysis. It would be especially interesting to study this topic for a specific demographic, a niche social media platform or online community, or a particular mental health condition.

Idea by computer science mentor Camille

Learn more about the Impact of Social Media on the Mental Health of Middle and High School Students

4. Formula 1 racing

Are you a fan of Formula 1 racing? Formula 1 is one of the most watched sports in the world! Extreme engineering, nail-biting precision, and excellent team dynamics are key to the participation and success of any team. The moment anyone decides to go rogue, the whole team is impacted - and may even be disqualified!

For those of you who enjoy working with data and have a little bit of data science and CS skills under your belt, an interesting project would be to analyze an F1 dataset and look at patterns in attributes like drivers, race times, season data, and pitstop status. For example, you can calculate correlations and regressions to better understand the relationships between those attributes.

Idea by computer science mentor Thomas

5. Analyzing cancer genomes

The Cancer Genome Atlas (TCGA) is a wealth of open-source data including patient health records, genomic sequencing and histology slides. You can analyze this data to calculate correlations between morphological histology, features, and mutations. Using machine learning, you can also predict patient survival based on histology or genomic data.

Focusing on a rare cancer would be ideal for this project as rare cancers tend to be understudied and even analyses utilizing small datasets could lead to interesting discoveries. There are multiple open source tools developed such as CLAM that you could use for this project.

Idea by computer science mentor Sharifa

7 Computer Science Projects in Machine Learning

1. introduction to sentiment analysis .

If you are brand new to machine learning, try using Python’s Natural Language Toolkit (NLTK) to analyze the text of your choosing! Sentiment analysis is a type of Natural Language Processing (NLP) that gives a number indicating whether a person feels positive, negative, or neutral towards what they’re talking about. For example, it can tell you how much a person did or did not like a movie based on a movie review.

In this project, you will begin by gathering text-based data. It’s best to use “real-world” data so that you can answer a research question! You can write your own text snippets in the code file, import some text that you have on your computer, or scrape data from online. To scrape (“collect”) data, you’ll use an API that allows you to easily get information from that website by using code, (e.g., the Reddit API ). Then, you’ll use the NLTK to analyze the text.

2. Continuing with sentiment analysis

You can do this project after the previous one about sentiment analysis, or you can dive straight in if you already have some programming experience. Try out developing your own sentiment analysis algorithms in this project. What are some words that indicate someone feels positive or negative towards a topic? How will you handle phrases with negative words, like “I didn’t like the movie.” Test how your algorithm compares to the NLTK!

3. Build a music or movie recommender

Have you ever been impressed with how websites like Netflix, Spotify, and Pandora seem to know what you enjoy? Doing a project where you build your own recommender is a great way to explore the various methods of content recommendation! You will learn concepts like content filtering, collaborative filtering, user/product embedding methods, graph-based techniques, and more. The goal of this project is for you to experiment with various types of recommenders and build your own for a product or media of your own choosing.

Idea by computer science mentor Eli

4. Detecting bots on Twitter

Bots are everywhere now! With fake news and bot detection becoming ever more important as a social and political issue, you might want to try your hand at a computer science bot detection project. You can do a project where you measure and quantify how easily it is to detect tweets that have been written by bots. You can start by going through the following four steps: 1) Collect some data, ideally labeled already as "fake.” 2) Observe properties of "real" vs. "fake" tweets. 3) Write a program (an example might be a Naive Bayes classifier ) to label new, incoming tweets as either “real” or “fake”. 4) Evaluate how good the program is using a sensible metric.

Idea by computer science mentor Clayton

5. Designing your own autocorrect algorithm

This is a project with two focal ideas - one in computer science and one in machine learning. The first idea is called dynamic programming and is one of the traditional ways in computer science to implement an autocorrect algorithm. Depending on your level, you can design it from scratch or just focus on the algorithm. After that, one option is to use machine learning to create different, personalized, and more accurate versions of autocorrect for individuals. The goal of this project is for you to get comfortable with a complex class of algorithms that are typically only learned in the later undergrad years!

Idea by computer science mentor Ryan

6. Guiding musicians with machine learning

If you’ve ever learned an instrument, you know how much help you need with tone quality, embouchure, managing hand placement, and pitch correction, among many other things! This is an advanced project where you will use your camera and microphone to explore ways to use machine learning and artificial intelligence to identify areas of improvement and suggest corrections. If you’ve been looking for ways to combine your interest in computer science and music, this is a great place to get started!

Idea by computer science mentor Ross

7. Natural language processing with BERT

Do you already have a good foundation in computer science? Did you recently develop a fascination with Natural Language Processing (NLP)? Well, this project might be the right one for you! In 2018, Google released BERT, a neural language model that helped NLP practitioners outperform previous state-of-the-art benchmarks in language tasks (e.g., question answering, sentiment analysis, machine translation) across the board.

You can do a project where you learn how deep learning researchers approach quantitative problems in classifying and analyzing language. You will develop an understanding of the concept of contextual word embeddings and the motivation for BERT. Last but not least, write code to apply BERT to a language task of your choosing! One example to get your creative juices flowing is quantifying gender bias in news articles or tweets.

Idea by computer science mentor Arnav

Start YOUR Computer Science Project

Research projects are great because they give you an edge on your college application . You may want to write a research paper after finishing your research. If research papers aren’t your thing, check out this list of creative ways you can explore your passions .

Check out the full Polygence student project database that has even more computer science research projects to inspire you!

Feeling Inspired?

Interested in doing an exciting research project? Click below to get matched with one of our expert mentors!

Upcoming Summer 2024 Application Deadline is May 12, 2024.

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25+ Research Ideas in Computer Science for High School Students

As a high school student, you may be wondering how to take your interest in computer science to the next level. One way to do so is by pursuing a research project. By conducting research in computer science, you can deepen your understanding of this field, gain valuable skills, and make a contribution to the broader community. With more colleges going test-optional, a great research project will also help you stand out in an authentic way!

Research experience can help you develop critical thinking, problem-solving, and communication skills. These skills are valuable not only in computer science but also in many other fields. Moreover, research experience can be a valuable asset when applying to college or for scholarships, as it demonstrates your intellectual curiosity and commitment to learning.

Ambitious high school students who are selected for the Lumiere Research Scholar Programs work on a research area of their interest and receive 1-1 mentorship by top Ph.D. scholars. Below, we share some of the research ideas that have been proposed by our research mentors – we hope they inspire you!

Topic 1: Generative AI

Tools such as ChatGPT, Jasper.ai, StableDiffusion and NeuralText have taken the world by storm. But this is just one major application of what AI is capable of accomplishing. These are deep learning-based models , a field of computer science that is inspired by the structure of the human brain and tries to build systems that can learn! AI is a vast field with substantial overlaps with machine learning , with multiple intersections with disciplines such as medicine, art, and other STEM subjects. You could pick any of the following topics (as an example) on which to base your research.

1. Research on how to use AI systems to create tools that augment human skills. For example, how to use AI to create detailed templates for websites, apps, and all sorts of technical and non-technical documentation

2. Research on how to create multi-modal systems. For example, use AI to create a chatbot that can allow users Q&A capabilities on the contents of a podcast series, a television show, and a very diverse range of content.

3. Research on how to use AI to create tools that can do automated checks for quality and ease of understanding for student essays and other natural language tasks. This can help students quickly improve their writing skills by improving the feedback mechanism.

4. Develop a computer vision system to monitor wildlife populations in a specific region.

5. Investigate the use of computer vision in detecting and diagnosing medical conditions from medical images.

6. Extracting fashion trends (or insert any other observable here) from public street scene data (i.e. Google Street View, dash cam datasets, etc.)

Ideas by a Lumiere Mentor from Cornell University.

Topic 2: Data Science

As a budding computer scientist, you must have studied the importance of sound, accurate data that can be used by computer systems for multiple uses. A good example of data science used in education is tools that help calculate your chances of admission to a particular college. By collecting a small amount of data from you, and by comparing it with a much larger database that has been refined and updated regularly, these tools effectively use data science to calculate acceptance rates for students in a matter of seconds.

Another area is Natural Language Processing, or NLP, for short, aims to understand and improve machines' ability to understand and interpret human language. Be it the auto-moderation of content on Reddit, or developing more helpful, intuitive chatbots, you can pick any research idea that you're interested in.

You could pick one of the following, or related questions to study, that come under the umbrella of data science.

7. Develop a predictive model to forecast traffic congestion in your city.

8. Analyze the relationship between social media usage and mental health outcomes in a specific demographic.

9. Investigate the use of data analytics in reducing energy consumption in commercial buildings.

10. Develop a chatbot that can answer questions about a specific topic or domain, such as healthcare or sports.

11. Learn the different machine learning and natural language processing methods to categorize text (e.g. Amazon reviews) as positive or negative.

12. Investigate the use of natural language processing techniques in sentiment analysis of social media data.

Ideas by a Lumiere Mentor from the University of California, Irvine.

Topic 3: Robotics

A perfect research area if you're interested in both engineering and computer science , robotics is a vast field with multiple real-world applications. Robotics as a research area is a lot more hands-on than the other topics covered in this blog, so it's a good idea to make a note of all the possible tools, guides, time, and space that you may need for the following ideas. You can also pitch some of these ideas to your school if equipped with a robotics lab so that you can conduct your research in the safety of your school, and also receive guidance from your teachers!

13. Design and build a robot that can perform a specific task, such as picking up and stacking blocks.

14. Investigate the use of robots in medicine, such as high-precision surgical robots.

15. Develop algorithms to enable a robot to navigate and interact with an unfamiliar environment.

Ideas by a Lumiere Mentor from University College London.

Topic 4: Ethics in computer science

With the rapid development of technology, ethics has become a significant area of study. Ethical principles and moral values in computer science can relate to the design, development, use, and impact of computer systems and technology. It involves analyzing the potential ethical implications of new technologies and considering how they may affect individuals, society, and the environment. Some of the key ethical issues in computer science include privacy, security, fairness, accountability, transparency, and responsibility. If this sounds interesting, you could consider the following topics:

16. Investigate fairness in machine learning. There is growing concern about the potential for machine learning algorithms to perpetuate and amplify biases in data. Research in this area could explore ways to ensure that machine learning models are fair and do not discriminate against certain groups of people.

17. Study the energy consumption and carbon footprint of machine learning can have significant environmental impacts. Research in this area could explore ways to make machine learning more energy-efficient and environmentally sustainable.

18. Conduct Privacy Impact Assessments for a variety of tools for identifying and evaluating the privacy risks associated with a particular technology or system.

Topic 5: Game Development

According to statistics, the number of gamers worldwide is expected to hit 3.32 billion by 2024. This leaves an enormous demand for innovation and research in the field of game design, an exciting field of research. You could explore the field from multiple viewpoints, such as backend game development, analysis of various games, user targeting, as well as using AI to build and improve gaming models. If you're a gamer, or someone interested in game design, pursuing ideas like the one below can be a great starting point for your research -

19. Design and build a serious game that teaches users about a specific topic, such as renewable energy or financial literacy.

20. Analyze the impact of different game mechanics on player engagement and enjoyment.

21. Develop an AI-powered game that can adjust difficulty based on player skill level.

Topic 6: Cybersecurity

According to past research, there are over 2,200 attacks each day which breaks down to nearly 1 cyberattack every 39 seconds. In a world where digital privacy is of utmost importance, research in the field of cybersecurity deals with improving security in online platforms, spotting malware and potential attacks, and protecting databases and systems from malware and cybercrime is an excellent, relevant area of research. Here are a few ideas you could explore -

22. Investigate the use of blockchain technology in enhancing cybersecurity in a specific industry or application.

23. Apply ML to solve real-world security challenges, detect malware, and build solutions to safeguard critical infrastructure.

24. Analyze the effectiveness of different biometric authentication methods in enhancing cybersecurity.

Ideas by Lumiere Mentor from Columbia University

Topic 7: Human-Computer Interaction

Human-Computer Interaction, or HCI, is a growing field in the world of research. As a high school student, tapping into the various applications of HCI-based research can be a fruitful path for further research in college. You can delve into fields such as medicine, marketing, and even design using tools developed using concepts in HCI. Here are a few research ideas that you could pick -

25. Research the use of color in user interfaces and how it affects user experience.

26. Investigate the use of machine learning in predicting and improving user satisfaction with a specific software application.

27. Develop a system to allow individuals with mobility impairments to control computers and mobile devices using eye tracking.

28. Use tools like WAVE or WebAIM to evaluate the accessibility of different websites

Topic 8: Computer Networks

Computer networks refer to the communication channels that allow multiple computers and other devices to connect and communicate with each other. An advantage of conducting research in the field of computer networks is that these networks span from local, regional, and other small-scale networks to global networks. This gives you a great amount of flexibility while scoping out your research, enabling you to study a particular region that is accessible to you and is achievable in terms of time, resources, and complexity. Here are a few ideas -

29. Investigate the use of software-defined networking in enhancing network security and performance.

30. Develop a network traffic classification system to detect and block malicious traffic.

31. Analyze the effectiveness of different network topology designs in reducing network latency and congestion.

Topic 9: Cryptography

Cryptography is the practice of secure communication in the presence of third parties or adversaries. It uses mathematical algorithms and protocols to transform plain text into a form that is unintelligible to unauthorized users - the process known as encryption.

Cryptography has grown in uses - starting from securing communication over the internet, protecting sensitive information like passwords and financial transactions, and securing digital signatures and certificates.

32. Investigating side-channel attacks that exploit weaknesses in the physical implementation of cryptographic systems.

33. Research techniques that can enable secure and private machine learning using cryptographic methods.

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Computer Science > Computation and Language

Title: researchagent: iterative research idea generation over scientific literature with large language models.

Abstract: Scientific Research, vital for improving human life, is hindered by its inherent complexity, slow pace, and the need for specialized experts. To enhance its productivity, we propose a ResearchAgent, a large language model-powered research idea writing agent, which automatically generates problems, methods, and experiment designs while iteratively refining them based on scientific literature. Specifically, starting with a core paper as the primary focus to generate ideas, our ResearchAgent is augmented not only with relevant publications through connecting information over an academic graph but also entities retrieved from an entity-centric knowledge store based on their underlying concepts, mined and shared across numerous papers. In addition, mirroring the human approach to iteratively improving ideas with peer discussions, we leverage multiple ReviewingAgents that provide reviews and feedback iteratively. Further, they are instantiated with human preference-aligned large language models whose criteria for evaluation are derived from actual human judgments. We experimentally validate our ResearchAgent on scientific publications across multiple disciplines, showcasing its effectiveness in generating novel, clear, and valid research ideas based on human and model-based evaluation results.

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arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

MyU : For Students, Faculty, and Staff

Fall 2024 CSCI Special Topics Courses

Cloud computing.

Meeting Time: 09:45 AM‑11:00 AM TTh Instructor: Ali Anwar Course Description: Cloud computing serves many large-scale applications ranging from search engines like Google to social networking websites like Facebook to online stores like Amazon. More recently, cloud computing has emerged as an essential technology to enable emerging fields such as Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning. The exponential growth of data availability and demands for security and speed has made the cloud computing paradigm necessary for reliable, financially economical, and scalable computation. The dynamicity and flexibility of Cloud computing have opened up many new forms of deploying applications on infrastructure that cloud service providers offer, such as renting of computation resources and serverless computing. This course will cover the fundamentals of cloud services management and cloud software development, including but not limited to design patterns, application programming interfaces, and underlying middleware technologies. More specifically, we will cover the topics of cloud computing service models, data centers resource management, task scheduling, resource virtualization, SLAs, cloud security, software defined networks and storage, cloud storage, and programming models. We will also discuss data center design and management strategies, which enable the economic and technological benefits of cloud computing. Lastly, we will study cloud storage concepts like data distribution, durability, consistency, and redundancy. Registration Prerequisites: CS upper div, CompE upper div., EE upper div., EE grad, ITI upper div., Univ. honors student, or dept. permission; no cr for grads in CSci. Complete the following Google form to request a permission number from the instructor ( https://forms.gle/6BvbUwEkBK41tPJ17 ).

CSCI 5980/8980

Machine learning for healthcare: concepts and applications.

Meeting Time: 11:15 AM‑12:30 PM TTh Instructor: Yogatheesan Varatharajah Course Description: Machine Learning is transforming healthcare. This course will introduce students to a range of healthcare problems that can be tackled using machine learning, different health data modalities, relevant machine learning paradigms, and the unique challenges presented by healthcare applications. Applications we will cover include risk stratification, disease progression modeling, precision medicine, diagnosis, prognosis, subtype discovery, and improving clinical workflows. We will also cover research topics such as explainability, causality, trust, robustness, and fairness.

Registration Prerequisites: CSCI 5521 or equivalent. Complete the following Google form to request a permission number from the instructor ( https://forms.gle/z8X9pVZfCWMpQQ6o6 ).

Visualization with AI

Meeting Time: 04:00 PM‑05:15 PM TTh Instructor: Qianwen Wang Course Description: This course aims to investigate how visualization techniques and AI technologies work together to enhance understanding, insights, or outcomes.

This is a seminar style course consisting of lectures, paper presentation, and interactive discussion of the selected papers. Students will also work on a group project where they propose a research idea, survey related studies, and present initial results.

This course will cover the application of visualization to better understand AI models and data, and the use of AI to improve visualization processes. Readings for the course cover papers from the top venues of AI, Visualization, and HCI, topics including AI explainability, reliability, and Human-AI collaboration. This course is designed for PhD students, Masters students, and advanced undergraduates who want to dig into research.

Registration Prerequisites: Complete the following Google form to request a permission number from the instructor ( https://forms.gle/YTF5EZFUbQRJhHBYA ). Although the class is primarily intended for PhD students, motivated juniors/seniors and MS students who are interested in this topic are welcome to apply, ensuring they detail their qualifications for the course.

Visualizations for Intelligent AR Systems

Meeting Time: 04:00 PM‑05:15 PM MW Instructor: Zhu-Tian Chen Course Description: This course aims to explore the role of Data Visualization as a pivotal interface for enhancing human-data and human-AI interactions within Augmented Reality (AR) systems, thereby transforming a broad spectrum of activities in both professional and daily contexts. Structured as a seminar, the course consists of two main components: the theoretical and conceptual foundations delivered through lectures, paper readings, and discussions; and the hands-on experience gained through small assignments and group projects. This class is designed to be highly interactive, and AR devices will be provided to facilitate hands-on learning. Participants will have the opportunity to experience AR systems, develop cutting-edge AR interfaces, explore AI integration, and apply human-centric design principles. The course is designed to advance students' technical skills in AR and AI, as well as their understanding of how these technologies can be leveraged to enrich human experiences across various domains. Students will be encouraged to create innovative projects with the potential for submission to research conferences.

Registration Prerequisites: Complete the following Google form to request a permission number from the instructor ( https://forms.gle/Y81FGaJivoqMQYtq5 ). Students are expected to have a solid foundation in either data visualization, computer graphics, computer vision, or HCI. Having expertise in all would be perfect! However, a robust interest and eagerness to delve into these subjects can be equally valuable, even though it means you need to learn some basic concepts independently.

Sustainable Computing: A Systems View

Meeting Time: 09:45 AM‑11:00 AM Instructor: Abhishek Chandra Course Description: In recent years, there has been a dramatic increase in the pervasiveness, scale, and distribution of computing infrastructure: ranging from cloud, HPC systems, and data centers to edge computing and pervasive computing in the form of micro-data centers, mobile phones, sensors, and IoT devices embedded in the environment around us. The growing amount of computing, storage, and networking demand leads to increased energy usage, carbon emissions, and natural resource consumption. To reduce their environmental impact, there is a growing need to make computing systems sustainable. In this course, we will examine sustainable computing from a systems perspective. We will examine a number of questions: • How can we design and build sustainable computing systems? • How can we manage resources efficiently? • What system software and algorithms can reduce computational needs? Topics of interest would include: • Sustainable system design and architectures • Sustainability-aware systems software and management • Sustainability in large-scale distributed computing (clouds, data centers, HPC) • Sustainability in dispersed computing (edge, mobile computing, sensors/IoT)

Registration Prerequisites: This course is targeted towards students with a strong interest in computer systems (Operating Systems, Distributed Systems, Networking, Databases, etc.). Background in Operating Systems (Equivalent of CSCI 5103) and basic understanding of Computer Networking (Equivalent of CSCI 4211) is required.

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BEST PROJECT TOPICS IN COMPUTER SCIENCE

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100+ Great Computer Science Research Topics Ideas for 2023
If you're searching for the best project topics for computer science students that will stand out in a journal, check below: Developments in human-computer interaction. Applications of computer science in medicine. Developments in artificial intelligence in image processing. Discuss cryptography and its applications.
Computer Science Research Topics (+ Free Webinar)
Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you've landed on this post, chances are you're looking for a computer science-related research topic, but aren't sure where to start.Here, we'll explore a variety of CompSci & IT-related research ideas and topic thought-starters ...
Undergraduate Research Topics
Online education, especially in Computer Science Education; Topics in research and development innovation methodologies including standards, open-source, and entrepreneurship; ... I am open to advise work on research projects in any topic in one of my research areas of interest. A project could also be based on writing a survey given results ...
500+ Computer Science Research Topics
Computer Science Research Topics are as follows: Using machine learning to detect and prevent cyber attacks. Developing algorithms for optimized resource allocation in cloud computing. Investigating the use of blockchain technology for secure and decentralized data storage. Developing intelligent chatbots for customer service.
Latest Computer Science Research Topics for 2024
It is not so easy to get your hands on the best research topics for computer science; spend some time and read about the following mind-boggling ideas before selecting one. 1. Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues, and Challenges.
Best Computer Science Project Topics: An Ultimate Guide
If you are in search of Computer Science Project Topics, this collection is just what you need to kickstart your journey. Discover a diverse collection of Computer Science Project Topics suitable for academic assignments, research projects, and real-world applications. Table of Contents . 1) Best Computer Science Project Topics . a) Face detection
Computer Science Projects
Computer Science Projects. Computer science is a popular topic of study today, with numerous applications spanning a wide range. Final-year students frequently find it difficult to select the appropriate computer science project. On the final day of graduation, projects are the only thing that matters. Any IT-related industry where projects ...
Computer Science Research Topics
These topics attempt to answer various computer science research questions and how they affect the tech industry and the larger world. Computer science research topics can be divided into several categories, such as artificial intelligence, big data and data science, human-computer interaction, security and privacy, and software engineering.
Research Projects
The CS department has resources available for research projects. The following is a quick start guide to research projects in Computer Science Department. This quick start guide does not cover all topics and it is recommended that you consult the CS Guide for more information. This guide is designed to help those beginning a research project by ...
Research projects
Text Analytics and Blog/Forum Analysis. Trustworthy Multi-source Learning (2025 entry onward) Verification Based Model Extraction Attack and Defence for Deep Neural Networks. Zero-Shot Learning and Applications. Search the postgraduate research projects currently available at The University of Manchester's Department of Computer Science.
On Undergraduate Research in Computer Science: Tips for shaping
The research should be on a topic of significant interest and related to things I have worked on, and one in which I have some intuition about the direction of research and conjectures that might be true and provable with elementary methods. ... As chair he led the development of the Brendan Iribe Center for Computer Science and Innovation, a ...
100+ Computer Science Topics: A Comprehensive Guide
Conclusion. Computer science is a field of limitless potential and continuous growth. It underpins the technology that powers our world and shapes the future. From the fundamentals of algorithms and data structures to the cutting-edge technologies of AI, quantum computing, and blockchain, computer science is a dynamic and ever-evolving discipline.
Top 30+ Computer Science Project Topics of 2024 [Source Code]
You will find projects for professionals, interns, freelancers, as well as final year projects for computer science. Top Computer Science Project Topics with Source Code. Source: crio.do. 1. Hospital Management System. Type: Application development, Database management, Programming. There is no shortage of computer science project topics out there.
Research Opportunities
Opportunities for undergraduates to conduct research in engineering, the applied sciences, and in related fields abound at Harvard. As part of your coursework, or perhaps as part of individual research opportunities working with professors, you will have the chance to take part in or participate in some extraordinary projects covering topics ...
Research project ideas for Computer Science students
2. Graphic simulator of programming structures and basic algorithms. This topic will result in a progressive web application that can show, graphically, what exactly is happening while the computer executes the following: Conditionals. Loops. Basic algorithms: counting, summing, maximum. Call to methods.
2020-2021 SURE Research Projects in CSE
The learning outcome for students will be hands-on experience in interdisciplinary research with connections to Machine Learning and Computational Economics. Expected research delivery mode: Remote. CSE Project #11: Hazel Notebooks: Building a Better Jupyter. Faculty Mentor: Cyrus Omar [comar @ umich.edu]
High School Computer Science Research: The Complete Guide ...
It's important to keep a few big-picture ideas in mind when we talk about computer science research. Research is an iterative process; we build on top of foundations (principles that act as building blocks or ways to think about problems). These are often mathematical in nature, and independent of our choice of programming language.
200+ Computer Science Research Project Ideas for College Students in
Interesting Computer Science Design Project Ideas for Finalists. Application of face detection technologies in crime deterrence. The role of an online auction system in preventing bribery. Application of computing technologies to improve academic performance. Shortcomings of the e-authentication systems.
Computer Science Research & Passion Project Ideas
Idea by computer science mentor Clayton. 5. Designing your own autocorrect algorithm. This is a project with two focal ideas - one in computer science and one in machine learning. The first idea is called dynamic programming and is one of the traditional ways in computer science to implement an autocorrect algorithm.
25+ Research Ideas in Computer Science for High School Students
This can help students quickly improve their writing skills by improving the feedback mechanism. 4. Develop a computer vision system to monitor wildlife populations in a specific region. 5. Investigate the use of computer vision in detecting and diagnosing medical conditions from medical images. 6.
12 Interesting Computer Science Project Ideas & Topics For ...
8. Symbol recognition. This is one of the excellent computer science project ideas for beginners. The proposed project seeks to build a system that can recognize symbols inserted by the user. This symbol recognition system leverages an image recognition algorithm to process images and identify symbols.
Computer Science Science Projects
Computer Science Science Projects. (56 results) From cell phones to social media, computer science is a part of your daily life. Everything from traffic lights to medical devices requires both computer hardware and software these days. Creative problem solvers are using computer science to tackle social problems, improve agriculture, make great ...
Research Projects
April 11th, 2024 Marcel Dall'Agnol joins the department as teaching faculty, bringing expertise in theoretical computer science; April 10th, 2024 Grad alum Avi Wigderson wins Turing Award for groundbreaking insights in computer science; April 9th, 2024 Computer science faculty recognized at the annual SEAS teaching awards
ResearchAgent: Iterative Research Idea Generation over Scientific
Scientific Research, vital for improving human life, is hindered by its inherent complexity, slow pace, and the need for specialized experts. To enhance its productivity, we propose a ResearchAgent, a large language model-powered research idea writing agent, which automatically generates problems, methods, and experiment designs while iteratively refining them based on scientific literature ...
Fall 2024 CSCI Special Topics Courses
Visualization with AI. Meeting Time: 04:00 PM‑05:15 PM TTh. Instructor: Qianwen Wang. Course Description: This course aims to investigate how visualization techniques and AI technologies work together to enhance understanding, insights, or outcomes. This is a seminar style course consisting of lectures, paper presentation, and interactive ...

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Best Computer Science Project Topics

Face detection

Crime rate prediction

E-authentication system

Online auction system

Evaluation of academic performance

Symbol recognition

Weather forecasting application

Public News Droid

Search engine

Online eBook master

Mobile wallet and merchant payment system

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2. The Influence of Extraction Methods on Big Data Mining

3. Integration of 5G with Analytics and Artificial Intelligence

4. Leveraging Asynchronous FPGAs for Crypto Acceleration

5. Cyber Security Future Technologies

6. Exploring the Boundaries Between Art, Media, and Information Technology

7. Evolution of Future Wireless Networks Using Cognitive Radio Networks

8. The Role of Quantum Computing and Machine Learning in Advancing Medical Predictive Systems

9. Implementing Privacy and Security in Wireless Networks

10. Exploring the Challenges and Potentials of Biometric Systems Using Computational Techniques

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