About me

I am a Researcher at Shanghai Artificial Intelligence Laboratory. I work on robotic learning and graph learning, with the goal of empowering embodied agents and autonomous vehicles to understand, reason about and react to complex interactions, covering motion prediction, planning, and generation; interaction representation and inference.

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 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

• [2026/04] LogitSpec accepted by ACL Findings’ 26.
• [2026/01] A paper on Human-Object-Scene Interaction Generation accepted by ICLR’ 26.
• [2025/08] We co-host a Multimodal Robot Learning Challenge in IROS 2025.
• [2025/06] GDPlan accepted by ToN and CSTA accepted by TCSVT.
• [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.

Selected Publications

Humanoid Motion

InfBaGel: Human-Object-Scene Interaction Generation with Dynamic Perception and Iterative Refinement

Yude Zou, Junji Gong, Xing Gao^✉, Zixuan Li, Tianxing Chen, and Guanjie Zheng
ICLR 2026
Project Page Paper

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation

Yuchen Yang, Xuanyi Liu, Xing Gao, Zhihang Zhong, and Xiao Sun
arXiv 2024
Paper

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
RA-L 2023
Paper

Graph Learning

iPool - Information-based Pooling in Hierarchical Graph Neural Networks

Xing Gao, Wenrui Dai, Chenglin Li, Hongkai Xiong, and Pascal Frossard
TNNLS 2021
Paper

Multiscale Representation Learning of Graph Data with Node Affinity

Xing Gao, Wenrui Dai, Chenglin Li, Hongkai Xiong, and Pascal Frossard
TSIPN 2020
Paper

GDPlan: Generative Network Planning via Graph Diffusion Model

Nuowen Kan, Sa Yan, Junni Zou, Wenrui Dai, Xing Gao, Chenglin Li, and Hongkai Xiong
ToN 2025
Paper