phd in computer science in tamil nadu

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Top PhD Computer Science Colleges in Tamil Nadu 2024

Found 76 Colleges Clear All

Selected Filters

• Tamil Nadu (76)
• Karnataka (54)
• Uttar Pradesh (32)
• Maharashtra (22)
• Rajasthan (18)
• Haryana (17)
• Madhya Pradesh (15)
• Gujarat (14)
• Andhra Pradesh (13)
• Punjab (12)
• Telangana (11)
• Odisha (10)
• Himachal Pradesh (9)
• Delhi NCR (9)
• Uttarakhand (8)
• Chhattisgarh (7)
• Jammu And Kashmir (6)
• West Bengal (6)
• Jharkhand (4)
• Meghalaya (3)
• Puducherry (3)
• Manipur (3)
• Mizoram (2)
• Arunachal Pradesh (2)
• Nagaland (1)
• Tripura (1)
• Coimbatore (29)
• Chennai (20)
• Tiruchirappalli (7)
• Namakkal (2)

Program Mode

• Offline (76)
• Private (48)
• Public (15)

Exams Accepted

• TANCET (20)
• JEE Main (4)
• JEE Advanced (1)
• CSIR NET (1)
• UGC NET (1)
• SRMJEEE (1)
• IIT JAM (1)

Course Type

• Doctorate (76)

Affiliated By

• Bharathiar University, [BU] Coimbatore (13)
• Anna University, Chennai (11)
• University of Madras, Chennai (7)
• University of Kalyani, Kalyani (1)
• University of Calcutta, [UC] Kolkata (1)
• SRMIST - SRM Institute of Science and Technology, Chennai (1)
• Madurai Kamaraj University, [MKU] Madurai (1)
• Less than 1 Lakh (19)
• 1 to 2 Lakhs (1)

Chennai, Tamil Nadu

The faculty are excellent and facilities provided by t... Read More

Average Fees

No. of Courses Offered

Median Salary

CAT, JEE Advanced

Bharathiar University

Coimbatore, Tamil Nadu

I am applying entrance exam applications date please s... Read More

CSIR NET, TANCET

Tiruchirappalli, Tamil Nadu

In this college professors are like what you’ll find in any o... Read More

CAT, JEE Main

Madras University

Hi friends , I completed My UG From Madras University in 2012 ... Read More

Alagappa University

Karaikudi, Tamil Nadu

The Quality of Teaching is excellent.The Professors are easily ... Read More

Sathyabama University

The quality and method of teaching is very poor in&nbs... Read More

Kalasalingam University

Krishnakoil, Tamil Nadu

During my stint ( 2010-14) for the first two years ,there we... Read More

Madurai Kamaraj University (MKU)

Madurai, Tamil Nadu

Daily timing are from 9am to 4pm, Good to study, ... Read More

My classes are really good. We are always engaged with... Read More

GATE, TANCET

Bannari Amman Institute of Technology

The academic schedule is 1.15 hours per subject and 5 ... Read More

TANCET, TNEA

Karunya University

High standards have been observed in this area. Anyone... Read More

Thiagarajar College of Engineering

The college has a very good set of faculty and peer group, a... Read More

NATA, TANCET

Sri Krishna College of Engineering and Technology

Last year least cut off for joining Sri Krishna college of e... Read More

B.S. Abdur Rahman Crescent Institute of Science and Technology

The admission to BCom and BSc (math, statistics, economics) ... Read More

• Infrastructure

Coimbatore Institute of Management and Technology (CIMAT)

Rajalakshmi Engineering College

Candidate must have passed the 12th from a recognized instit... Read More

Indian Institute of Knowledge Management

• Scholarship

CIT Coimbatore

- The syllabus has been updated and it is extraordinary. The co... Read More

R.M.K. Engineering College

Tiruvallur, Tamil Nadu

The class timing is from 8:30 am to 03:50 pm at R... Read More

S.A. Engineering College

Teaching is good ... Read More

Dr. N.G.P. Arts & Science College (DRNGPASC)

Candidates are given admission into Dr.NGP College of ... Read More

Saveetha Engineering College

The class timing is from 9:30 am to 3:30 pm at Sa... Read More

Dr. SNS Rajalakshmi College of Arts and Science

The eligibility criterion is 12th pass and should have mathe... Read More

Bishop Heber College

The college which I've studied is good in all activit... Read More

Jamal Mohamed College, [JMC] Tiruchirappalli

The eligibility criteria for Jamal Mohamed College is ... Read More

Nehru Arts and Science College Coimbatore

The internships were extra ordinary and well worth with a di... Read More

SCSVMV Kanchi University

Kanchipuram, Tamil Nadu

The quality and method of teaching are very good by al... Read More

AISEEE, ATMA

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Chennai Mathematical Institute

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The Department of Computer Science is one among the science departments of this University that offers M.Sc. Computer Science, full time four semester program spread over two years started from the academic year 2016 – 2017. The program provides a solid theoretical foundation through high quality teaching complemented by extensive practical learning. It is committed to impart quality education in all fields of IT, a field growing in leaps and bounds.

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• One-day National Workshop on “Computational Intelligence Using Machine Learning”
• PhD Thesis Pre-submission Seminar – Mr.Kalivara Prasanna Babu (R181302)
• Fisherwomen Mobile App – Project report on “A Study and Development of Mobile App for Fisherwomen in Nagapattinam District to Reduce Complexities for Selling of Fishes”
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• A Five Day Faculty Development Programme on Fundamentals of Data Science – A Practical Approach

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• PRAGNA – Vol. I | Issue 01 | July 2020
• PRAGNA – Vol. II | Issue 01 | August 2021

To develop the department as a global leader in knowledge dissemination and to perform cutting edge research in computer science in compliance with international standards

• To excel in transforming graduates into software experts with high degree of technical creativity and managerial skills
• To excel in imparting quality education using innovative best practices
• To train the students to take up various challenges of latest technologies in the field of computer science

Programmes Offered

M.sc. computer science, eligibility criteria:.

M.Sc. (Two Year) Computer Science The Department of Computer Science comes under the School of Mathematics and Computer Sciences that offers M.Sc. Computer Science, full-time four-semester program spread over two years started from the academic year 2016 – 2017. The program provides a solid theoretical foundation through high-quality teaching complemented by extensive practical learning. It is committed to impart quality education in all fields of IT, a field growing by leaps and bounds.

The program aims to provide the foundation for a professional career in the computing-based industries, to afford a foundation for basic and applied computer science engineering research and to acquire concrete knowledge in reasoning methods, design and implementation techniques. The curriculum is so designed to meet the standards expected from the IT industry and to those students who aspire for research. The Department offers Choice Based Credit Systems (CBCS) which enable students to choose electives from other departments. The students are evaluated for courses through Continuous Assessment Scheme (CAS).

Duration of the programme: Two Years (Four Semesters)

Mode of selection: cuet score, sanctioned strength: 26, curriculum:, post graduate diploma in data science.

A regular Bachelor’s degree in Computer Applications/Computer Science/Mathematics/or any Bachelor’s degree in Science stream with core Mathematics as one of the subjects for at least four semesters. Candidates should have secured a minimum of 60% marks or 6.5 CGPA (on a 10-point scale) in the qualifying degree examination for General Category, 55% marks or 6.0 CGPA (on a 10 point scale) for EWS/OBC (Non-creamy layer) and 50% aggregate marks or 5.5 CGPA (on a 10-point scale) for SC/ST/PWD candidates

Duration of the programme: One Year

Sanctioned strength: 9, ph.d. computer science.

A consistently good academic record and possessing a Degree in Computer Science / Information Technology or allied subjects, obtained from a recognized University/Institute or Foreign University equivalent (approved by AIU).

Dr. Chandra Mouli P.V.S.S.R.

Associate Professor & Head

Email: [email protected]

Dr. Prema Mayudu B

Associate Professor

Email: [email protected]

Dr. P. Thiyagarajan

Assistant Professor

Email: [email protected]

Dr. K. Nandhini

Email: [email protected]

Dr. R. Saranya

Email: [email protected]

Dr. A. Martin

Email: [email protected]

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List of Mentor and Mentee

Students achievements.

• Mr.Muhammed Niyas, K.P. Ph.D. Scholar (Full time) under the guidance of Dr.P.Thiyagarajan has cleared UGC NET in November 2017 (Roll No: 36002995)
• Mr.Rahul Kumar (M.Sc. Computer Science II year) have participated and won second prize in Debugging Competition conducted by National Institute of Technology, Puducherry during 24-26 February 2017.

No. of Publications:

H-index of the department:, i-10 index of the department:, no. of citations:.

Head of the Department Department of Computer Science Central University of Tamil Nadu Thiruvarur – 610 005 Phone : +91-4366-277230 Email : [email protected]

Prize distribution – Enlish Literary cranival pegasus 2023

MOU between CUTN and DCO – Census data research work station

International Day of Yoga 2023

Workshop Epigraphy and Heritage Management

Community College of CUTN Signs MOU with ELGI Equipments Limited

Tree Planting Drive at CUTN

1700 Saplings will be planted in CUTN

Mathematics Conference at CUTN

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45 Best universities for Computer Science in Tamil Nadu

Updated: February 29, 2024

• Art & Design
• Computer Science
• Engineering
• Environmental Science
• Liberal Arts & Social Sciences
• Mathematics

Below is a list of best universities in Tamil Nadu ranked based on their research performance in Computer Science. A graph of 1.3M citations received by 163K academic papers made by 45 universities in Tamil Nadu was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Indian Institute of Technology Madras

For Computer Science

2. VIT University

3. Anna University

4. Amrita University

5. National Institute of Technology, Tiruchirappalli

6. SRM Institute of Science and Technology

7. Sathyabama Institute of Science and Technology

8. Annamalai University

9. SASTRA University

10. Karunya Institute of Technology and Sciences

11. Saveetha University

12. Bharathiar University

13. Kalasalingam University

14. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

15. University of Madras

16. Bharathidasan University

17. Hindustan Institute of Technology and Science

18. Karpagam Academy of Higher Education

19. Alagappa University

20. Manonmaniam Sundaranar University

21. Sri Ramachandra Institute of Higher Education and Research

22. Gandhigram Rural University

23. B.S. Abdur Rahman Crescent Institute of Science and Technology

24. Madurai Kamaraj University

25. Periyar University

26. Vels University

27. Dr. M.G.R. Educational and Research Institute

28. Indian Institute of Information Technology, Design and Manufacturing

29. Bharath Institute of Higher Education and Research

30. Chennai Mathematical Institute

31. Avinashilingam University

32. SCSVMV University

33. Tamil Nadu Agricultural University

34. Thiruvalluvar University

35. Vinayaka Missions University

36. Mother Teresa Women's University

37. Meenakshi Academy of Higher Education and Research

38. central university of tamil nadu.

39. Tamil University

40. Periyar Maniammai Institute of Science and Technology

41. Tamil Nadu Dr. M.G.R.Medical University

42. Ponnaiyan Ramajayam Institute of Science and Technology

43. Tamil Nadu Veterinary and Animal Sciences University

44. Tamil Nadu Dr. J. Jayalalithaa Fisheries University

45. Indian Maritime University

Closest to Tamil Nadu states to learn Computer Science

Computer science subfields in tamil nadu.

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• UTCS Direct

Five Computer Science Students Named 2024 College of Natural Sciences Dean’s Honored Graduates

Submitted by Anonymous on Fri, 05/03/2024 - 10:00am

The title of Dean’s Honored Graduate is the highest honor a College of Natural Sciences student can receive. Each year, graduating seniors are nominated by faculty members for their achievements in research, academics, community building and service to the college. This year’s graduating seniors will receive recognition at the May 11 college ceremonies.

Meet the graduating UT Computer Science seniors being recognized for excellence in research, academics, and improving the community.

Alex Burton

Dean’s honored graduate in mathematics and computer science.

Alex Burton is a Turing Scholar from Austin, Texas, graduating with degrees in mathematics and computer science. As a passionate student of both math and computer science, his research interests are in applied cryptography, which lies at the intersection of these two fields. His work in applied cryptography focuses on bridging the gap between theoretical frameworks and practical efficiency. His honors thesis with David Wu applies both algebraic and systems-level optimizations to improve the concrete efficiency of private information retrieval schemes. He is currently working towards extending the work in his thesis to be published in ACM CCS, a top cybersecurity conference. He has previously been an undergraduate course assistant for discrete math, where he takes pride in helping his fellow students. Outside of class, whether he is lifting in Gregory Gym, jogging around Austin or hiking in the remote wilderness, Burton embraces physical challenges as much as intellectual ones. After graduation, he will continue his research in applied cryptography at UT Austin in the five-year master’s program. In the future, he hopes that he can keep using his talents to keep the world of digital information free and secure.

Stephane Hatgis-Kessell 

Dean’s honored graduate in computer science.

Stephane Hatgis-Kessell is graduating with a B.S. in computer science, with Turing Scholars Honors. For the last 3 years, he has worked with Brad Knox, Peter Stone and Scott Niekum on understanding how to learn human-aligned behaviors for decision-making systems from human data. Hatgis-Kessell has co-authored a conference paper, entitled “Learning optimal advantage from preferences and mistaking it for reward,” and a journal paper entitled “Models of human preference for learning reward functions.” For his research, Hatgis-Kessell received the UT Co-Op George H. Mitchell Award and was selected for Honorable Mention of the 2024 Computing Research Association’s Outstanding Undergraduate Researcher Award. He is excited to continue developing new methods for ensuring that intelligent agents do what we actually want them to do as a Ph.D. student at Stanford University. Outside of his academic pursuits, Hatgis-Kessell has enjoyed backpacking through Asia for the last four months. 

Jenn Mickel

Dean’s honored graduate in computer science and mathematics.

Jennifer Mickel is a Turing Scholar and Polymathic Scholar, graduating with degrees in computer science and mathematics, as well as minors in African and African diaspora studies, sociology, and women and gender studies. During her time at UT, Mickel worked on research in artificial intelligence fairness, where she used sociological insights to uncover biases in AI systems, develop fair algorithms, and outline intersectionally-informed model development choices. Her work has been accepted to the ACM Conference on Fairness, Accountability and Transparency. Mickel has worked with Maria De-Arteaga and Sina Fazelpour on understanding diversity considerations during dataset development and with Kevin Tian on developing algorithms to improve group performance in demographic-free settings. She has also worked with Hugging Face to understand the social impact of existing evaluations for generative AI. Her Polymathic Scholars honors thesis was titled  “The Importance of Multi-dimensional Intersectionality in Algorithmic Fairness and AI Model Development.” In addition to her research contributions, Mickel was co-president of the Turing Scholars Student Association and led ACM for Change’s DEI initiative, where she worked to improve the experiences of underrepresented groups within computer science. Following graduation, Mickel intends to pursue graduate school and continue her research in AI fairness.

Leo Orshansky

Leo Orshansky is graduating with a B.S. in computer science and a B.S. in mathematics, and with Turing Scholars honors. In addition, he is receiving a minor in Chinese. He grew up in Austin, Texas, and has been passionate about solving problems in computer science and mathematics from the moment he came to UT Austin. Since 2022, he has been an undergraduate researcher in the unconventional computing theory group at UT led by David Soloveichik, where he contributed to the group’s work on DNA computing and zero-energy computing. Two of his research results were featured in the DNA29 conference, with one receiving the Best Student Presentation Award. He has been recognized as a CNS Honors Scholar in his sophomore year and received the Outstanding Chinese Language Student award in his junior year. In Fall 2023, he defended a computer science honors thesis with the title “Computation in Isolated Thermodynamic Systems.” He recently received the NSF Graduate Research Fellowship, which will fund his ongoing and future research in theoretical computer science for three years of graduate school. Outside of his academic life, he enjoys running with the Texas Running Club, playing racquetball and solving crossword puzzles. After graduation, Orshansky will pursue a Ph.D. in theoretical computer science at Columbia University.

Shankar Padmanabhan

Dean’s honored graduate in mathematics.

Shankar Padmanabhan is a graduating Dean’s Scholar earning a B.S in mathematics with honors and the elements of computing certificate. Since Fall 2022, Padmanabhan has worked with Eunsol Choi and Greg Durrett in the Department of Computer Science on developing methods that enable language models such as ChatGPT to be lifelong learners. His work has resulted in publications presented at top machine learning conferences, including Neural Information Processing Systems (NeurIPS) 2023 and Association for Computational Linguistics (ACL) 2023. In the short term, Padmanabhan is interested in working towards a better understanding of when and how language models learn from data. In the long term, he wants to deeply understand the foundations of intelligence. Padmanabhan has also earned the CRA Undergraduate Researcher Award Honorable Mention, the Eva Stevenson Woods Presidential Scholarship and an NSF Graduate Research Fellowship. Outside of research, Padmanabhan has played for UT’s club ultimate frisbee team and enjoys learning new languages. After graduation, Padmanabhan will pursue a Ph.D. in computer science, specializing in natural language processing at Cornell University. He is grateful for his time at UT and for the support of his professors.

Read the full  2024 College of Natural Sciences Dean’s Honored Graduates story written by Esther Robards-Forbes

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Nevada Today

Father and son set to receive doctoral degrees May 17

College of Engineering will graduate Jay and Nathan Thom with Ph.Ds in Computer Science & Engineering

Interest in computer science runs in the family.

There’s nothing like 700-level computer science classes to bring on the father-son bonding: just ask Jay and Nathan Thom.

Jay will be receiving a doctorate in Computer Science & Engineering at the May 17 Engineering graduation ceremony, and so will his son, Nathan.

“Graduating with a Ph.D. is a really satisfying accomplishment for me, but graduating with one of my sons will make it one of the most memorable experiences of my life,” said Jay, who also works in the College of Engineering’s Computer Science & Engineering Department as a senior information security engineer.

The two studied together, supported each other and maybe once or twice Jay kept Nathan on track.

“He was a good influence,” Nathan, who goes by Nate, said. “He was the friend you needed to have.”

When Nate joined the University of Nevada, Reno in 2015, Jay helped him with calculus. Years later, Nate would return the favor when Jay needed help with the math in a game theory class. The two have shared lab space and even co-authored two conference papers about Internet of Things (IoT) device identification.

Additional co-authors on those papers were Professor Shamik Sengupta and Assistant Professor Emily Hand, each of whom served as Ph.D. advisors for Jay and Nate, respectively.

“Jay and Nate have been extremely helpful, cooperative and hardworking people,” Sengupta said. “They are extremely friendly and always ready to help on a moment’s notice.”

Sengupta added that Jay will be his 10 th   Ph.D. student to graduate; for Hand, the experience of mentoring a Ph.D. student through graduation is new.

“Nate has been wonderful to work with,” she said. “He and Jay both have been an asset to the (CSE) department and college. They serve as our resident IT guys, helping with anything and everything in our labs.”

Anomaly in the data set

Parent-child graduations are somewhat unusual, but not for Jay. In 2015, he received his Bachelor of Science degree alongside his son Ben. 

Also out of the ordinary: Jay was a teaching assistant for a class in which his two other sons, Max and Nick, were students.

Nate, the youngest, remembers hanging out with his brothers on the University campus even before he enrolled as a student. When he was 13, Nate was homeschooled by Jay, and would tag along with his father to the University and study on campus. His three older brothers also were students at that time, and as Nate remembers, “Mom had just graduated.”

“Mom” is Shendry Thom, who earned bachelor’s, master’s and doctoral degrees in nursing from the University.

And of course, the University is where Shendry met Jay, back in the 1980s.

The campus has been somewhat of a stomping ground for the Thom family.

“It feels like home,” Nate said.

Family affair

If campus feels like home, computer science is where everyone seems to gather: Nate’s older brothers Ben, Max and Nick are software engineers in the Reno area; Nate’s wife Kathleen currently studies computer science at the University; and Nick’s fiancé, Maddy, is pursuing a master’s degree in computer science, also at the University. Jay might be responsible for this family trend, according to Nate.

Jay originally studied electrical engineering in the 1980s, but when he returned to the University to study computer science, Nate said, “that was the same year Max had started college. That influenced him and me. We’re all in computer science.”

Their areas of expertise vary, however. Jay’s dissertation, “AI Enabled IOT Network Traffic Fingerprinting with Locality Sensitive Hashing,” deals with training smart devices to communicate with each other securely. Nate’s dissertation, “Attributes in Face Processing: Novel Methods for Explanation, Training and Representation,” is about improving AI systems that recognize faces.

What they have in common — besides genetics — is a strong interest in advancing the field of computer science.

“We’re really good at coming up with big ideas,” Nate said. “One of the things we say is ‘create value.’ Every time we show up somewhere, we try to create value.”

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Six Students Awarded NSF Graduate Research Fellowships

The five-year fellowship is awarded to outstanding students pursuing a graduate degree in stem.

Northwestern Engineering PhD students Mandi Cai, Melissa Chen, Lawrence Chillrud, Fiona Neylon, and Essien Taylor, and undergraduate student Carolyn Zou in Northwestern’s School of Communication, have been awarded National Science Foundation (NSF) Graduate Research Fellowships in recognition of their demonstrated potential for significant research achievements.

The highly selective Graduate Research Fellowship program awards a five-year fellowship to outstanding individuals pursuing a full-time, research-based graduate degree in science, technology, engineering, and mathematics (STEM) disciplines. The students will receive three years of financial support, including an annual stipend.

Prior to joining Northwestern, Cai was a data journalist at The Texas Tribune . Her award-winning work with editors Darla Cameron and Chris Essig inspired Cai’s curiosity about data visualizations in the media and shaped her current research focus.

“This fellowship provides me with the support to investigate all the big, pressing questions I had while working as a data journalist — ‘how is data journalism supporting the public’s ability to understand and interact with data, data visualizations, and statistical models in news coverage around high-profile topics like COVID-19 and elections? How do audiences understand and trust this coverage?’” Cai said.

Leading up to the November elections, she is investigating public perceptions around the use of data and statistical modeling in elections coverage, with a particular focus on the communication of live election results and winner projections. Cai and her collaborators — Kay and Erik Nisbet , Owen L. Coon Endowed Professor of Policy Analysis, and Communication — aim to determine participants’ baseline level of understanding, points of confusion, and degree of distrust toward winner projections in US elections. Using this data, the team will design and test alternative explanations of projections to improve user understanding and synthesize techniques for newsrooms to effectively communicate data-driven models.

“Ultimately, I wish to empower data journalists to be data educators who can consider the unique needs of their reader populations,” Cai said. “I also seek to empower readers to understand data they encounter in everyday life. More public data and statistical literacy supports individuals in evaluating and interrogating data as it is used to guide decisions or fuel algorithms.”

Melissa Chen

Chen studies students’ self-efficacy — or a person's belief in their ability to complete a task or achieve a goal — in introductory computing courses.

Building on research by O’Rourke and Jamie Gorson (PhD ’22), a graduate of the joint PhD program in Computer Science and Learning Sciences , Chen is examining students’ self-assessments during the process of learning programming and the tendency for novice programming students to be self-critical. Chen wants to understand how students with lower self-efficacy are influenced by personal experiences and interactions with the computing community and aims to design scalable systems that help students adjust their self-assessment criteria to be more aligned with what is expected of them as computing learners.

“Self-efficacy has an impact on students’ decisions to persist in computing,” Chen said. “By gaining a better understanding of how to improve and build self-efficacy, I hope to be able to equitably support students so that they feel confident learning and using their computing skills in their everyday lives.”

Supported by a 2023-24 Design Cluster research fellowship, Chen is also working on a related project with O’Rourke and Duri Long , assistant professor of communication studies in the School of Communication and (by courtesy) assistant professor of computer science at Northwestern Engineering. The team is designing a socially situated, small-group intervention to help students reframe their self-assessments and improve their self-efficacy. They plan to work with students to determine how to make the interventions scalable.

Lawrence Chillrud

Chillrud is developing machine learning methods for applications in biomedical imaging. He aims to create robust uncertainty quantification techniques for medical imaging models and to design reliable algorithms that can assist doctors and patients in making informed decisions.

“Knowing when to trust these complex predictive models in high-stakes clinical settings is of critical importance,” Chillrud said. “If a model could reliably estimate its case-by-case uncertainty, clinicians could have a better understanding of how to integrate model predictions in data-driven decision-making, and patients could be better informed and in control of their disease and treatment plan.”

Chillrud is working on two research projects. In his radiological work, he is developing models that seek to predict the presence or absence of important brain tumor biomarkers in a patient’s MRI scan. In pathology, Chillrud is investigating computational techniques to help renal pathologists identify patients most at risk of kidney transplant failure.

Chillrud earned a bachelor’s degree in computer science from Columbia University in 2020. Prior to joining Northwestern, Chillrud was a senior programmer in the Department of Environmental Health Sciences at Columbia University’s Mailman School of Public Health. His research into the development of interpretable machine learning methods for assessing complex mixtures of environmental exposures in epidemiological studies with mentor Marianthi-Anna Kioumourtzoglou ignited Chillrud’s passion for research and inspired him to pursue a PhD.

“I feel tremendously lucky to have been awarded the fellowship and believe that it speaks more to the exceptional support and mentorship I have received over the years from advisers, colleagues, teachers, friends, and family, than it does say anything about me personally,” Chillrud said. “I am also hugely grateful to the NSF for their support during this early and exciting stage of my career.

Katsaggelos is the Joseph Cummings Professor of Electrical and Computer Engineering and (by courtesy) professor of computer Science at Northwestern Engineering and professor of radiology at Northwestern’s Feinberg School of Medicine . Cooper is the director of the Institute for Artificial Intelligence in Medicine’s Center for Computational Imaging and Signal Analytics in Medicine and associate professor of pathology and preventive medicine at Feinberg and (by courtesy) associate professor of electrical and computer engineering.

Fiona Neylon

Neylon’s research interests lie in human-robot interaction in the medical, rehabilitation, and assistive spheres. Drawing from her own prolonged rehabilitation experience during high school after a near-total spinal fusion, she aims to develop tools that clinicians and patients can use to improve overall quality of life.

“Having normal function one day and limited the next made me understand the importance of independence and improving the quality of life for all,” Neylon said. “I’m thankful for being in the unique position of pairing that experience with my technical training to make me the researcher I am today — one motivated to improve the lives of individuals through robotic and assistive solutions.”

After joining Argall’s Assistive and Rehabilitation Robotics Laboratory (argallab) at the Shirley Ryan AbilityLab in 2022, Neylon began working with the argallab’s assistive robotic arm project team on developing a body-machine interface for customized control. The group is studying the learning effects of individuals with spinal cord injuries to control a seven-degree-of-freedom robotic arm via a shared control training paradigm.

“Receiving the fellowship is an incredible honor and is not only validation of the dedication I’ve put into my academic and research pursuits, but also a testament to the support of my mentors,” Neylon said.

Essien Taylor

Taylor investigates computer architecture and aims to reduce energy consumption in power-constrained embedded systems, including electronic medical implants and mobile phones.

“Understanding the energy consumption of microprocessors requires detailed models that take a large amount of time and labor to create,” Taylor said. “My current work will generate these complex models in a fraction of the time and effort, allowing us to rapidly explore countless research avenues.”

In 2023, the financial support of his GEM Fellowship afforded Taylor the opportunity to intern with Cadence Design Systems Inc., which aided his approach to electronics design.

Taylor is also a member of the Karsh STEM Scholars Program at Howard University, where he earned a bachelor’s degree in computer engineering. The program provides full scholarships for undergraduate students in science, technology, engineering, and mathematics disciplines and support for underrepresented minorities completing graduate programs in STEM.

“My experience as a Karsh STEM Scholar at Howard University was crucial in developing my passion for research,” Taylor said.

Carolyn Zou

Zou builds AI tools that support the design of resilient social systems. Leveraging generative language models, her goal is to create ‘agents’ that faithfully represent the people that populate complex social systems.

“Simulations with these agents can reflect the contingent dynamics of social influence and interaction, and prototyping with populated systems allows decision-makers to assess the anticipated effects of, and iterate on, prosocial interventions,” Zou said.

This fall, Zou will join the PhD program in computer science at Stanford University, supported by both the NSF Graduate Research Fellowship and a Stanford Graduate Fellowship.

"I am immensely grateful for the NSF's support as I begin my graduate studies. This recognition is a testament to the incredible mentorship I've received at Northwestern and truly speaks to the opportunities afforded by the wide reach of human-computer interaction research across the University,” Zou said. “Northwestern's interdisciplinary environment allowed me to pursue HCI research from a starting point in the social sciences while developing the technical skills to prepare me for a PhD in computer science, and I look forward to bringing this unique perspective to my future work in human-AI interaction."

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May 16 (Thu) @9:00am: "On the Role of Information in the Control of Multi-Agent Systems: A Game-Theoretic Approach," Bryce Ferguson, ECE PhD Defense

With an influx of many new communication and computation technologies, many systems that once existed in isolation now interact and form the basis of large multi-agent systems (e.g., fleets of drones/robots or human drivers with live-traffic routing apps). Though this advance in scale and connectivity offers many opportunities, a major challenge comes from the fact that the emergent system behavior induced by many local decisions need not be optimal. As a method to elicit greater coordination, we can design how individual system components behave, or we can design how they communicate with one another. I will discuss several ways in which information-communication channels can be exploited as a method to control overall system behavior. Particularly, I will present a game-theoretic model for distributed decision-making and demonstrate the possible benefits and costs of increasing communication in terms of gain/loss to equilibrium efficiency and solution complexity.

Bryce L. Ferguson is a PhD candidate in the Electrical and Computer Engineering Department at the University of California, Santa Barbara. Bryce received his BS and MS in Electrical Engineering from the University of California, Santa Barbara in June 2018 and March 2020, respectively, and his A.A. in Mathematics from Santa Rosa Junior College in 2016. He was named a 2022 CPS Rising Star and was a finalist for the Best Student Paper Award at the 2020 American Controls Conference. Bryce's research interests focus on using game theoretic methods for describing and controlling both social and engineered multi-agent systems. Hosted by : Professor Jason Marden Submitted by : Bryce Ferguson < [email protected] >

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