About me

I am a Researcher at Shanghai Artificial Intelligence Laboratory. My research focuses on graph learning, robotics learning, and autonomous driving. I have explored various applications of graph learning in autonomous driving, sports, and physical simulations.

I received my Ph.D. degree in Electronic Engineering from Shanghai Jiao Tong University (SJTU), advised by Prof. Hongkai Xiong. From 2018 to 2019, I was a visiting Ph.D. student at the Signal Processing Laboratory (LTS4) at École Polytechnique Fédérale de Lausanne (EPFL), co-supervised by Prof. Pascal Frossard. Before that, I achieved my B.S. in Electronic Engineering from Shanghai Jiao Tong University, receiving the the SJTU Outstanding Bachelor’s Thesis (Top 1%).

I warmly welcome interested students and interns to reach out via email if you are interested in collaboration!

News

• [2025/08] We co-host a Multimodal Robot Learning Challenge in IROS 2025.
• [2025/02] Our AI tactical prediction system for curling was successfully applied at 2025 Asian Winter Games, featured on CCTV-16 and reported by Xinhua News Agency.
• [2025/01] IntSim accepted by ICRA’ 25.
• [2024/05] ProgD ranks 1st on the INTERACTION Multi-agent Leaderboard.

Selected Publications

Autonomous Driving

Safety-Critical Traffic Simulation with Adversarial Transfer of Driving Intentions

Zherui Huang, Xing Gao^✉, Guanjie Zheng^✉, Licheng Wen, Xuemeng Yang, and Xiao Sun
ICRA 2025
Project Page Paper

SceneDM: Consistent Diffusion Models for Coherent Multi-agent Trajectory Generation

Zhiming Guo, Xing Gao^✉, Jianlan Zhou, Xinyu Cai, Xuemeng Yang, Licheng Wen, and Xiao Sun
CASE 2025
Project Page Paper

Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networks

Xing Gao, Xiaogang Jia, Yikang Li, and Hongkai Xiong
RAL 2023
Paper