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I am a Ph.D. student at University of Pennsylvania, where I am advised by Professor George J. Pappas. I am affiliated with the GRASP Lab and PRECISE Center. Previously, I obtained my Bachelor's degree (Summa Cum Laude) from Shanghai Jiao Tong University in 2021 and I worked closely with Professor Xiang Yin. I have also spent time at Toyota Research and Tencent AI. I am broadly interested in formal methods, machine learning, control theory, and algorithmic game theory, with their applications to robotic and multi-agents systems. In the past, my work mainly cover
Email / Linkedin / CV / Github / Google Scholar / GRASP Page |
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[Jul 2024] Our paper on Conformal Off-Policy Prediction is accepted by CDC 2024. [May 2024] I co-organized the 2nd Workshop on MAD-Games: Multi-Agent Dynamic Games at ICRA 2024, Japan. [Apr 2024] Glad to hear that I am selected as a 2024 DAAD AInet Fellow on Safe and Secure AI. [Mar 2024] I wrote a simple and easy-to-use Nash Equilibrium Solver for Two-Player Zero-Sum games, feel free to play around with it. [Jan 2024] Our paper on Learning Adaptive Safety is accepted by ICRA 2024. [Jan 2024] New work on Learning Local Safety Filters for Hybrid Systems [preprint][code]. [Jan 2024] I give a talk at CMU Intelligent Control Lab. [Jan 2024] Our paper on Safe Hybrid System is accepted by ACC 2024. [Dec 2023] Selected as a Global Young PhD Fellow of Linear Capital. [Dec 2023] I am invited to be an Area Chair of Tiny Papers @ ICLR 2024. [Sep 2023] I give a talk at UPenn ASSET Seminar with Rahul. [Sep 2023] Invited talk at UPenn Formal Methods & Machine Learning Seminar. [Jul 2023] I give a talk at UMich Prof. Necmiye Ozay's group. |
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(* indicates equal contribution) |
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Bridging the Gap between Discrete Agent Strategies in Game Theory and Continuous Motion Planning in Dynamic Environments
Learning Local Control Barrier Functions for Safety Control of Hybrid Systems
Multi-agent reinforcement learning guided by signal temporal logic specifications
Conformal Off-Policy Prediction for Multi-Agent Systems
MEGA-DAgger: Imitation learning with multiple imperfect experts
Learning Adaptive Safety for Multi-Agent Systems
Shuo Yang, Mitchell Black, Georgios Fainekos, Bardh Hoxha, Hideki Okamoto, Rahul Mangharam American Control Conference (ACC) 2024 [PDF][code]
Safe perception-based control under stochastic sensor uncertainty using conformal prediction
You don't know when I will arrive: unpredictable controller synthesis for temporal logic tasks
A benchmark comparison of imitation learning-based control policies for autonomous racing
Differentiable safe controller design through control barrier functions
Verification and Synthesis of Opacity for Cyber-Physical Systems
Secure your intention: On notions of pre-opacity in discrete-event systems
Opacity of networked supervisory control systems over insecure communication channels
Secure-by-construction optimal path planning for linear temporal logic tasks
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University of Pennsylvania, Philadelphia, PA, USA Tencent AI, Shenzhen, China Toyota Research Institute of North America, Ann Arbor, MI, USA Duke University, remote Shanghai Jiao Tong University, Shanghai, China |
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