Xinjie Liu
Hello and welcome! I am a second-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
news
Oct 16, 2024 | We submitted Policies with Sparse Inter-Agent Dependencies in Dynamic Games: A Dynamic Programming Approach! |
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Aug 17, 2024 | Our paper Auto-Encoding Bayesian Inverse Games was accepted to WAFR 2024. See you in Chicago! |
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) |