Sudeep Sarkar

S. Sarkar

Distinguished University Professor and Department Chair

ENB 345 | 813-974-2113

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Sudeep Sarkar is a Distinguished University Professor, Chair of Computer Science and Engineering at the University of South Florida, Tampa, and Co-Director of the USF Institute for Artificial Intelligence + X. He received his M.S. and Ph.D. in electrical engineering on a University Presidential Fellowship from The Ohio State University, Columbus, and his B. Tech degree from the Indian Institute of Technology, Kanpur. 

He has 35 years of experience conducting and directing fundamental research in computer vision, predictive learning, biometrics, and artificial intelligence. His use-inspired contributions are in systems to recognize persons from how they walk (gait biometrics), automated recognition of actions, activities, and events in a video, economic activity from satellite images, and extracting precise medically relevant information from medical images.  He has directed 22 Doctoral and 25 Master's students on these topics.

He is a co-Editor-in-Chief of Pattern Recognition Letters and was the President of the IEEE Biometrics Council. He is a Fellow of the National Academy of Inventors (NAI), American Association for the Advancement of Science (AAAS), American Institute of Medical and Biological Engineers (AIMBE), Institute of Electrical and Electronics Engineers (IEEE), and International Association for Pattern Recognition (IAPR) and member of the Academy of Science, Engineering, and Medicine of Florida. He was the recipient of the National Science Foundation CAREER award in 1994, the USF Teaching Incentive Program Award for Undergraduate Teaching Excellence in 1997, the Outstanding Undergraduate Teaching Award in 1998, the Theodore and Venette Askounes-Ashford Distinguished Scholar Award in 2004, and William R. Jones Outstanding Mentor Award, 2017.

Research Interests

Prof. Sudeep Sarkar is an internationally recognized researcher. His research contributions have been in artificial intelligence (AI), specifically AI involving images and videos, i.e., computer vision. Computer vision involves inferring a scene's content, geometry, and motion from images and videos. Prof. Sarkar's research style involves intertwining fundamental research and use-inspired research. He has made seminal contributions to the problem of perceptual organization and grouping in computer vision, including introducing Bayesian networks, graph spectral methods, and supervised machine learning. He has also made significant contributions to biometrics, particularly gait recognition, which involves recognizing someone from how they walk. His benchmark for gait recognition is a de facto standard in the field. Prof. Sarkar is a strong collaborator and has bridged computer science with various disciplines, such as psychology, linguistics, medicine, civil engineering, mechanical engineering, industrial engineering, and mathematics.

Since 2014, Dr. Sarkar's research has focused on developing next-generation AI technology based on neuro-symbolic formalisms, particularly in event understanding and computer vision. He has worked on multiple NSF-funded projects to build computer vision/AI algorithms to anticipate and proactively assist with daily living activities, such as using a robotic arm on a wheelchair. This technology also has applications in constructing smart spaces for independent living and monitoring wildlife. Dr. Sarkar's approach to event understanding combines symbolic and deep learning using Grenander's canonical representations, which has led to the development of self-supervised streaming algorithms that require little or no supervision. His research received numerous awards, including the best scientific paper award in 2014 and a large collaborative grant from NSF in 2020. Dr. Sarkar is also involved in use-inspired research to detect economic recovery markers from satellite imagery and has built an AI solution to detect flying airplanes over a 2300 square miles area around each of the 30 busiest European airports using satellite images, which won the top prize in a competition organized by the European Space Agency. Additionally, Dr. Sarkar's inventions have resulted in ten US patents, and one of his technologies has been licensed to a startup bought by a major corporation.

Teaching Interests

Data structures, advanced data structures, computer vision, pattern recognition, image-based biometrics, probabilistic models, ethics in computing, image processing, medical imaging, and computational geometry. Also, over the past years, we have developed image-related knowledge units, assignments, and software that can be used for introducing image-related tasks in undergraduate data structures and algorithms.


PhD in Electrical Engineering, Ohio State University (1993)
MS in Electrical Engineering, Ohio State University (1990)
BT in Electrical Engineering, Indian Institute of Technology, India (1988)

Honors and Awards

  • Distinguished University Professor, 2021.
  • Member of the Academy of Science, Engineering, and Medicine of Florida, 2021.
  • William R. Jones Outstanding Mentor Awards, Florida Education Fund, 2017.
  • Fellow of the National Academy of Inventors (NAI), 2017.
  • Fellow of the American Institute for Medical and Biological Engineering (AIMBE), 2016.
  • Fellow of the American Association for the Advancement of Sciences (AAAS), 2013.
  • Fellow of the Institute for Electrical and Electronics Engineering (IEEE), 2013.
  • Fellow of the International Association of Pattern Recognition (IAPR), 2008.
  • Askounes-Ashford Distinguished Scholar Award, University of South Florida, 2004. 
  • Outstanding Undergraduate Teaching Award, University of South Florida, 1998. 
  • Teaching Incentive Program Award, University of South Florida, 1996. 
  • CAREER Award, National Science Foundation, 1995. 

Key Activities

Apart from his administrative duties as a chair, Dr. Sarkar is currently engaged in extensive externally funded research. Current research grants (as PI or Co-PI) total more than $9 million. The grants cover cybersecurity, computer science, engineering, and robotics. The largest grant is for Testing & Evaluation for Soldier-Device Teaming Compatibility, Vulnerability, and Durability in Emergent Situations, funded by the US Army DEVCOM Data & Analysis Center (DAC)/KRI Northeastern. Other grants are funded by the National Science Foundation (NSF), Intelligence Advanced Research Projects Activity (IARPA), and various departments within the state of Florida. These grants aim to broaden computer science and engineering participation, enhance cybersecurity awareness, and achieve autonomy by learning from sensor-assisted control in a wheelchair-based human-robot collaborative system.

He has served in various leadership capacities, including chairing or serving as a member of various committees, boards, and organizations related to computer vision, pattern recognition, biometrics, and other fields. The current activities under this section include General Co-Chair of the Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2023, and General Co-Chair of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. Since 2011, he is also an Editor in Chief for Pattern Recognition Letters.