Stefanos Nikolaidis is an Assistant Professor of Computer Science at the University of Southern California. His research draws upon expertise on artificial intelligence, procedural content generation and quality diversity optimization and leads to end-to-end solutions that enable deployed robotic systems to act robustly when interacting with people in practical, real-world applications. Stefanos completed his PhD at CMU's Robotics Institute and received an MS from MIT, a MEng from the University of Tokyo and a BS from the National Technical University of Athens. Stefanos' research has been recognized with an NSF CAREER award, an oral presentation at NeurIPS and best paper awards and nominations from HRI, IROS, and ISR.
Varun Bhatt is a Ph.D. student with Prof. Stefanos Nikolaidis in the Computer Science department at USC. His general research goal is to understand and develop algorithms for efficient robot-robot and robot-human interactions using ideas from reinforcement learning and game theory. He completed his B.Tech at the Indian Institute of Technology Bombay and his M.Sc. at the University of Alberta. During his master's, he worked with Prof. Michael Buro on an algorithm for multi-agent communication.
Robby is a PhD student in the CS department at USC, currently advised by Prof. Stefanos Nikolaidis, with previous guidance from Prof. Fei Sha and Prof. Maja Matarić. Prior to joining ICAROS he gained experience at Google Brain as a student researcher, completed his B.S. at Columbia University where he was advised by Prof. Junfeng Yang, and participated in multiple NSF-funded summer REU programs through which he was introduced to CS research. Robby’s current research focuses on enhancing reinforcement learning agents’ abilities to adapt and generalize over complex task distributions by introducing various structural inductive biases. His goal is to reduce the need for significant human supervision which current AI methods rely on heavily.
Nathan is a Ph.D. student in the computer science department at USC. He is co-advised by Prof. Maja Matarić and Prof. Stefanos Nikolaidis. Nathan previously received a B.S. in Computer Science and a B.Eng. in Robotics Engineering from Worcester Polytechnic Institute. Nathan is an NSF Graduate Research Fellow and a USC Annenberg Fellow. Their current area of research is in how users can adapt robotic systems to their specific needs and preferences, specifically in the context of users with limited mobility.
Matt Fontaine is a PhD student at the University of Southern California advised by Stefanos Nikolaidis. Prior to coming to USC, Matt completed B.S. and M.S. degree at the University of Central Florida. He also worked as a research assistant in game-based training at UCF’s Institute for Simulation and Training and as a simulation engineer at Drive.ai. His research interests are broadly in the intersection of automatic scenario generation for training, procedural content generation in games, and human-robot interaction.
Ya-Chuan (Sophie) Hsu is a PhD student advised by Prof. Stefanos Nikolaidis in the Department of Computer Science at the University of Southern California. She received her M.S degree in Computer Science from Texas A&M University, where she was advised by Prof. Dylan Shell. She has broad research interests in robotics and artificial intelligence. Her current research has been centered on planning under uncertainty, particularly behavior planning for human-aware robots.
Aniruddh is a Ph.D. student in the computer science department at USC. He is co-advised by Prof. Jyotirmoy Deshmukh and Prof. Stefanos Nikolaidis. Prior to his PhD, he was a researcher in connected vehicles at Toyota R&D. He previously received a masters in Computer Science (Intelligent Robotics) from USC. His research is at the intersection of formal methods (temporal logics and verification), and robotics (learning from demonstrations and deep reinforcement learning) for guaranteeing safety and efficiency in human-robot interactions.
Bryon Tjanaka is a Ph.D. candidate in the ICAROS Lab at USC advised by Stefanos Nikolaidis. Bryon researches robotics and AI, particularly applications of quality diversity optimization to reinforcement learning and human-robot collaboration. Bryon is an NSF Graduate Research Fellow and a USC Graduate School Fellow. Previously, Bryon studied at UC Irvine, where he worked with the indylab and the Mobley Lab and graduated summa cum laude. Concurrent with his research, Bryon serves as webmaster for the Viterbi Graduate Student Association, and he has interned at Google for several summers. During high school, Bryon won the VEX Robotics World Championship with Team 86868.
Hejia is a computer science PhD student at the Interactive and Collaborative Autonomous Robotic Systems Lab advised by Prof. Stefanos Nikolaidis at University of Southern California. His research interests lie in ways robots can actively acquire knowledge from non-expert human users, vast amount of available online content and interacting with the environment to intelligently plan and act in real-world applications while alongside and interacting with humans. His research is motivated by real-world problems in domestic and field robotics and targets at eventually enabling robots to help ordinary people in their daily life and replace human workers in dangerous environments.
Shihan is a Ph.D. student in the Computer Science department at USC, advised by Prof. Stefanos Nikolaidis. He received his M.S. in computer science from USC, and B.A. in computer science/cognitive science from Vassar College. He is currently interested in quality-diversity optimization and its role in facilitating machine learning generalization.
Yutai is a Ph.D. student in the Department of Computer Science advised by Prof. Stefanos Nikolaidis at USC. He completed his B.S. at the University of Florida, and worked as a machine learning researcher at MIT Lincoln Laboratory, where he helped create the lab's reinforcement learning research group (MeRLin). He also collaborated with the Stanford Intelligent Systems Laboratory, under the guidance of Prof. Mykel Kochenderfer. His research interest centers around cooperative AI, with particular focus on multiagent reinforcement learning, quality-diversity optimization, and algorithmic scenario generation, with applications to human-robot interaction. Outside of the lab, he is passionate about powerlifting and traveling.
Naren is a Masters student in Computer Science (Intelligent Robotics) at USC. Prior to USC, Naren worked on the development of efficient and accurate perception systems for autonomous vehicles at NVIDIA. He received his B.S. in Computer Engineering from the University of Illinois Urbana-Champaign where he was advised by Prof. Derek Hoiem performing research on multi-view 3D reconstruction methods and Prof. Tim Bretl working on robotic manipulation of elastic materials. In high school, he worked under Prof. Nikolas Correll on human - swarm interfaces. His current research interests center on methods for developing collaborative embodied agents drawing ideas from reinforcement learning, quality diversity optimization, and human - robot interaction.
Hi! I’m Allen. I am pursuing a CSCI B.S., AMCM B.S. @ USC. I am the Co-President of CAIS++, and I’ve previously been at the MIT Haystack Observatory, and Tsinghua University. I enjoy thinking about cooperative AI. My research interests include human-computer interaction, explainable AI, and multimodal learning.
David Lee is an undergraduate student majoring in Computer Science at the University of Southern California. At ICAROS, he is working on developing and maintaining the open source quality diversity library known as pyribs. His research interest is in quality diversity and optimization.
Hi, I'm Anisha! I am currently an undergraduate studying Computer Engineering and Computer Science. Here at ICAROS, I work on designing cool new quality diversity algorithms that improve performance and resilience in complex robotics tasks. My research interests lie at the intersection of evolutionary algorithms, reinforcement learning, and AI for robotics. Outside of research, I enjoy teaching fun CS concepts and exploring classic cinema.
Peter Wang is an undergraduate student majoring in Computer Engineering and Computer Science (CECS) and Applied Math at the University of Southern California. His research focuses on learning and planning for multi-robot and human-robot systems and developing robotics that solve real-world problems. His areas of interest are control, task and motion planning, and reinforcement learning.
Ph.D. 2022 (visiting Ph.D. student from University of Washington working with Siddhartha Srinivasa), Motion Planning Engineeer at Motional
Ph.D. 2020 (co-advised by Prof. C.-C. Jay Kuo), Applied Scientist at Amazon Research