Sandip Sen, Ph.D. - The University of Tulsa
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Sandip Sen, Ph.D.

Professor of Computer Science


Sandip Sen is a professor in the Tandy School of Computer Science with primary research interests in artificial intelligence, intelligent agents, machine learning, and evolutionary computation. He completed his Ph.D. on intelligent, distributed scheduling from the University of Michigan in December, 1993. He has authored approximately 300 papers in workshops, conferences, and journals in several areas of artificial intelligence. He received the prestigious NSF CAREER award in 1997. He has served on the program committees of major national and international conferences in the field of intelligent agents including AAAI, IJCAI, AAMAS, GECCO, etc. He regularly reviews papers for major AI journals and serves on the proposal review panels of the National Science Foundation. He has chaired multiple conferences, workshops and symposia on agent learning and reasoning. He has presented several tutorials on different multiagent systems topics in association with the leading international conferences on intelligent agents. He was elected to the position of Senior Member in the professional organization of AI researchers, the Association for the Advancement of Artificial Intelligence (AAAI), in 2014. He has been recognized with a lifetime Outstanding Researcher Award by The University of Tulsa in May, 2023.

Awards and Honors

  • 2023 Outstanding Research Award, The University of Tulsa
  • 2014 AAAI Senior Member
  • 2014 Outstanding TURC Mentor Award, The University of Tulsa
  • 1999 Outstanding Research Award, College of Engineering & Natural Sciences, The University of Tulsa
  • 1997 CAREER Award, National Science Foundation


  • Ph.D., Computer Science and Engineering, University of Michigan, Ann Arbor, 1993
  • M.S., Electrical Engineering, University of Alabama, Tuscaloosa, 1988
  • B.E., Electronics & Tele-communications Engineering, Jadavpur University,1986

Research interests and areas of expertise

  • Artificial intelligence
  • Machine learning
  • Intelligent agents
  • Evolutionary computation