Glen received dual B.S. degrees in Electrical Engineering & Computer Science and Mechanical Engineering from UC Berkeley in 2017 and M.S. and Ph.D. degrees in Electrical & Computer Engineering from the University of Michigan in 2019 and 2022, respectively. Prior to joining Georgia Tech as an assistant professor in 2024, Glen spent two years as a postdoc at MIT CSAIL.
Glen directs the Trustworthy Robotics Lab, which focuses on the design of algorithms that can enable general-purpose robots and autonomous systems to operate capably, safely, and securely, while remaining resilient to real-world failures and uncertainty. To achieve this, the lab leverages control theory and machine learning, while connecting to optimization, perception, formal methods, motion planning, human-robot interaction, and statistics. Glen is interested in all aspects of robot algorithm design - including creating the algorithms themselves, proving their properties, and deploying them on real robots.
- Robotics
- Trustworthy autonomy
- Machine learning
- Control theory
- Optimization
- Human-robot interaction
- Robotics: Science & Systems Pioneer, 2022
- National Defense Science and Engineering Graduate (NDSEG) Fellowship, 2019
- National Science Foundation (NSF) Graduate Fellowship, 2019
- G. Chou, N. Ozay, D. Berenson. Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory, Workshop on the Algorithmic Foundations of Robotics (WAFR), 2022.
- G. Chou, N. Ozay, D. Berenson. Learning Temporal Logic Formulas from Suboptimal Demonstrations: Theory and Experiments. Autonomous Robots (AURO), 2022.
C. Knuth*, G. Chou*, N. Ozay, D. Berenson. Planning with Learned Dynamics: Probabilistic Guarantees on Safety and Reachability via Lipschitz Constants. Robotics & Automation Letters (RA-L), 2021. - G. Chou, N. Ozay, D. Berenson. Learning Constraints from Locally-Optimal Demonstrations under Cost Function Uncertainty. Robotics & Automation Letters (RA-L), 2020.
- G. Chou*, Y. Sahin*, L. Yang*, K. Rutledge, P. Nilsson, N. Ozay. Using Control Synthesis to Generate Corner Cases: A Case Study on Autonomous Driving. International Conference on Embedded Software (EMSOFT), 2018.