Xinjie Liu


Hello and welcome! I am a first-year Ph.D. student in the Department of Electrical and Computer Engineering, Cockrell School of Engineering at The University of Texas at Austin. I am very fortunate to be co-advised by Prof. Ufuk Topcu and Prof. David Fridovich-Keil. My research interests lie in theoretical foundations and deployable practical decision-making and control strategies for autonomous systems in dynamic and uncertain environments. I am currently focused on intelligent, safe interactions of robots with other agents and efficient robot control policy learning.

I obtained a master’s degree (the highest cum laude distinction) in Robotics from the Department of Cognitive Robotics (CoR) at the Delft University of Technology, Netherlands, where I was very fortunate to be advised by Prof. Javier Alonso-Mora. My master’s thesis was on game-theoretic motion planning for multi-agent systems. Before that, I received my bachelor’s degree in Automotive Engineering from Tongji University, Shanghai. During my senior year, I studied as a visiting undergraduate student at the Graz Univerisity of Technology, Austria.

Keywords: robotics, optimization, control theory, dynamic game theory, reinforcement learning


May 29, 2024 An open-source project on implementation of numerical optimization algorithms.
May 22, 2024 We submitted Second-Order Algorithms for Finding Local Nash Equilibria in Zero-Sum Games!
Feb 2, 2024 We submitted Auto-Encoding Bayesian Inverse Games!
Jul 10, 2023 Graduated from TU Delft! I successfully defended my thesis and obtained my MSc degree with Cum Laude distinction in Robotics [slides]!
Jul 5, 2023 I gave a talk at the Control and Learning for Autonomous Robotics (CLeAR) Lab, UT Austin!
Apr 17, 2023 Our paper “Learning to Play Trajectory Games Against Opponents with Unknown Objectives” has been accepted at the IEEE Robotics and Automation Letters (RA-L) and will be presented at IROS 2023. See you in Detroit!
Jan 24, 2023 I gave an invited talk at the Safe Robotics Laboratory, Princeton [slides]. Thanks for the invitation!
Dec 1, 2022 Our work “Learning to Play Trajectory Games Against Opponents with Unknown Objectives” has been submitted and is now available! Please check out the preprint version here.
Jun 30, 2022 We won the Hackathon challenge at the European Robotics Forum 2022! (Post from the sponsor Franka Emika)