I am a Ph.D. student in the Paul G. Allen School of Computer Science & Engineering, University of Washington. I built, trained and worked with Geodude, a customized dexterous bimanual robot. I am affiliated with UW Robotics.
Before joining UW, I was a mechanical engineer in Africa. Prior to that, I was a researcher at Carnegie Mellon University, advised by Prof. Christopher Atkeson and Prof. Katerina Fragkiadaki. I graduated with High Honors from Zhejiang University, where I earned my bachelor's degree in Computer Science and minored in Electronic Engineering.
My work is
Robotics, Embodied AI, Multimodal LLM
Humanoid robotic manipulation
Physical Embodied AI
Human-robot interaction and alignment
SAPIEN: A SimulAted Part-based Interactive ENvironment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X.Chang, Leonidas J. Guibas, Hao Su
CVPR 2020,Oral Presentation
[Paper] [Project] [Video]We build SAPIEN simulator: an interaction-rich and physics-realistic simulation environment integrating PhysX engine and ROS control interface. I lead the team of building SAPIEN dataset: more than 2K 3D articulated models with 14K movable parts. The dataset is richly annotated with kinematic part motions and dynamic interactive attributes to support robot interaction.
S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes
Yuzhe Qin*, Rui Chen*, Hao Zhu, Meng Song, Jing Xu, Hao Su (*Equal contribution)
CoRL 2019,Spotlight Presentation
[Paper] [Project] [Video] [Presentation]We studied the problem of 6-DoF grasping by a parallel gripper in a cluttered scene captured using a commodity depth sensor from a single view point. Our learning based approach trained in a synthetic scene can work well in real-world scenarios, with improved speed and success rate compared with state-of-the-arts.
CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark
Jiefeng Li, Can Wang, Hao Zhu, Yihuan Mao, Hao-Shu Fang, Cewu Lu
CVPR 2019,Oral Presentation
[Paper] [Code] [Dataset] [Media]We collect CrowdPose, a new dataset of crowded human poses. We propose a joint-candidate single person pose estimation (SPPE) and a global maximum joints association algorithm to tacklethe problem of pose estimation in a crowd. Our method surpasses the state-of-the-art method by 5.2 mAP on CrowdPose and replacing certain steps in the state-of-the-art method with our module would bring 0.8 mAP improvement on MSCOCO.
Trivia
Hobbies
Cooking I cook in a western style, but with Chinese flavors. I'll open my own restaurant one day.
Games I am good at strategy games, board games, poker games, etc.
Music I enjoy classical music and electronic music, especially trance and techno. My faves: I play the piano and suona.
Trading I consider myself a proficient trader in options and day trading. I achieved a 20x profit in 2 weeks in mid-2024.