Stefanos Nikolaidis

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Assistant Professor of Computer Science


  • 2018, Doctoral Degree, Robotics, Carnegie-Mellon University
  • 2014, Master's Degree, Aeronautics and Astronautics, Massachusetts Institute of Technology
  • 2009, Master's Degree, Precision Engineering, University of Tokyo
  • 2006, Bachelor's Degree, Electrical and Computer Engineering, National Technical University of Athens


Stefanos Nikolaidis is an Assistant Professor of Computer Science at the University of Southern California. His research focuses on the mathematical foundations of human-robot interaction, drawing upon expertise on machine learning, algorithmic game theory and decision making under uncertainty. His work leads to end-to-end solutions that enable deployed robotic systems to act optimally when interacting with people in practical, real-world applications. Previously, Stefanos completed his PhD at Carnegie Mellon's Robotics Institute and received his MS from MIT. He has also a MEng from the University of Tokyo and a BS from the National Technical University of Athens. Stefanos has worked as a research associate at the University of Washington, as a research specialist at MIT and as a researcher at Square Enix in Tokyo. He has received a Best Enabling Technologies Paper Award from the IEEE/ACM International Conference on Human-Robot Interaction in 2015, a best paper nomination from the same conference in 2018 and was a best paper award finalist in the International Symposium on Robotics 2013.

Research Summary

Stefanos Nikolaidis directs the Interactive and Collaborative Autonomous Robotic Systems (ICAROS) lab, which focuses on the core computational challenges in human-robot interaction: what are good models of human behavior, how to learn such models from noisy samples, and how to robustly generate actions for robotic teammates in large scale real-world applications. Research in ICAROS spans the whole spectrum of human-robot interaction science: from distilling the fundamental mathematical principles that govern interactive behaviors, to developing approximation algorithms for deployed robotic systems and testing them "in the wild" with actual end users.

  • Computer Science

  • SAL 104
  • USC Mail Code: 0781

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