About me

I am currently a PhD student in the Department of Electrical and Electronics Engineering at The University of Hong Kong, advised by Prof. Yanchao Yang. Before that, I obtained my Bachelor’s degree from School of EECS, Peking University. My research interest lies in the intersection between computer vision and robotics.

During my undergraduate study, I am very fortunate to be advised by Prof. Hao Dong who leads the PKU-Agibot Lab at Peking University, China.

Publications

COLA: Learning Human-Humanoid Coordination for Collaborative Object Carrying
Yushi Du*, Yixuan Li*, Baoxiong Jia*, Yutang Lin, Pei Zhou, Wei Liang, Yanchao Yang, Siyuan Huang
We present COLA, a proprioception-only reinforcement learning approach that unifies leader and follower behaviors within a single policy. Trained in a closed-loop environment modeling dynamic interactions among humanoid, object, and human, COLA implicitly predicts object motion to enable compliant collaboration and maintain load balance.
ICRA2026

VER: Vision expert transformer for robot learning via foundation distillation and dynamic routing
Yixiao Wang, Mingxiao Huo, Zhixuan Liang, Yushi Du, Lingfeng Sun, Haotian Lin, Jinghuan Shang, Chensheng Peng, Mohit Bansal, Mingyu Ding†, Masayoshi Tomizuka
We propose VER, a Vision Expert transformer for Robot learning. We further introduce Patchwise Expert Routing with Curriculum Top-K Annealing to improve both flexibility and precision of dynamic expert selection. Moreover, VER supports parameter-efficient finetuning for scalable expert utilization and robot-domain knowledge integration.
ICLR2026

Learning Part Motion of Articulated Objects Using Spatially Continuous Neural Implicit Representations
Yushi Du*, Ruihai Wu*, Yan Shen, Hao Dong
We introduce a novel framework that explicitly disentangles the part motion of articulated objects by predicting the movements of articulated parts by utilizing spatially continuous neural implicit representations.
code
BMVC2023

Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly
Ruihai Wu*, Chenrui Tie*, Yushi Du, Yan Shen, Hao Dong
We study geometric shape assembly by leveraging SE(3) Equivariance, which disentangles poses and shapes of fractured parts.
code
ICCV2023