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; VLA and WAM; 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%) and Outstanding Graduate of Shanghai.

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

News

• [2026/06] An agentic framework for open-world mobile manipulation REAL accepted by ECCV’26.
• [2026/05] EmbodiedClaw accepted by CVPR MARS Workshop’26.
• [2026/05] We have released a 24/7 online mobile manipulation benchmark EBench.
• [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 IEEE ToN and CSTA accepted by IEEE 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

Manipulation

Exploratory, Communicative, and Deployable: Vision-Driven Embodied Agents for Open-World Mobile Manipulation

Boyu Mi, Mengchen Ma, Yifei Yao, Xing Gao^✉, Junting Chen, Yangzi Li, Zihou Zhu, Guohao Li, Zhenfei Yin, Tai Wang, Yao Mu, Jiangmiao Pang, Hanqing Wang^✉
ECCV 2026
Project Page Paper Code

Ebench: Elemental Diagnosis of Generalist Mobile Manipulation Policies

Ning Gao, Jinliang Zheng, Xing Gao, Haoxiang Ma, Hanqing Wang, Yukai Wang, Jiantong Chen, Zanxin Chen, Shujie Zhang, Mingda Jia, Xuekun Jiang, Zihou Zhu, Xinyu Li, Shuai Wang, Hao Li, Wenzhe Cai, Yuqiang Yang, Xudong Xu, Zhaoyang Lyu, Yao Mu, Tai Wang, Jiangmiao Pang, Jia Zeng, Weinan Zhang, Chunhua Shen
arXiv 2026
Project Page Paper Code

InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization

Haoxiang Ma, Junhao Cai, Xiaoxu Xu, Hao Li, Yuyin Yang, Yang Tian, Jiafei Cao, Hongrui Zhu, Zherui Qiu, Yuqiang Yang, Jiaqi Peng, Xueyuan Wei, Yangkun Zhu, Jiahao Jiang, Xing Gao, Hanqing Wang, Feng Yuan, Kailin Li, Xueyue Zhu, Tai Wang, Yan Ding, Jiangmiao Pang, Jia Zeng, Jingjing Zhang, Bowen Zhou, Yao Mu, Chunhua Shen, Weinan Zhang
arXiv 2026
Project Page Paper Code

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

Joint Multi-agent Motion Forecasting via Progressive Multi-scale Decoding over Dynamic Graphs

Xing Gao, Zherui Huang
IROS 2026
Paper

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

Realistic Rainy Weather Simulation for LiDARs in CARLA Simulator

Donglin Yang, Xinyu Cai, Zhenfeng Liu, Wentao Jiang, Bo Zhang, Guohang Yan, Xing Gao, Si Liu, Botian Shi
IROS 2024
Paper

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

Xing Gao, Xiaogang Jia, Yikang Li, and Hongkai Xiong
IEEE 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
IEEE TNNLS 2021
Paper

Multiscale Representation Learning of Graph Data with Node Affinity

Xing Gao, Wenrui Dai, Chenglin Li, Hongkai Xiong, and Pascal Frossard
IEEE 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
IEEE ToN 2025
Paper