Xinjie Liu

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Hello and welcome! I am a third-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 develops theoretical foundations and practical algorithms for decision making and control in autonomous systems under uncertainty. I am currently focused on (i) efficient and scalable reinforcement learning through principled integration of data from multiple sources, and (ii) intelligent and safe interaction for multi-agent systems, such as robots operating in shared environments. The majority of my work draws on reinforcement learning, numerical optimization, game theory, and statistical estimation and inference.

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.


news

Oct 15, 2025 Our paper “Inferring Foresightedness in Dynamic Noncooperative Games” has been accepted at the IEEE Robotics and Automation Letters (RA-L) and will be presented at ICRA 2026!
Sep 29, 2025 We submitted A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation!
May 23, 2025 I presented Policies with Sparse Inter-Agent Dependencies in Dynamic Games: A Dynamic Programming Approach at AAMAS 2025, Detroit! We submitted an extended version of this work to IEEE Transactions on Automatic Control (T-AC).
Apr 11, 2025 I’m honored to have received a travel grant from Texas Robotics!
Oct 16, 2024 We submitted Policies with Sparse Inter-Agent Dependencies in Dynamic Games: A Dynamic Programming Approach!
Oct 9, 2024 I’m honored to have received a travel grant from WAFR 2024 and to have presented our work Auto-Encoding Bayesian Inverse Games. It was a lot of fun in Chicago!
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)