Han Xue

薛晗 | Han Xue

I am a first-year Ph.D. student at the College of AI, Tsinghua University, advised by Prof. Li Yi. My research is supported by GALBOT. I received my B.E. in Computer Science from Tsinghua University.

My research focuses on enabling humanoid robots to acquire complex real-world skills in a scalable and sustainable manner. I am particularly interested in moving beyond motion imitation toward automated generation and effective utilization of multi-source data.

CV / Email / Scholar / Github

Tracking targets, even in dreams.

Research

	Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data Zhikai Zhang, Haofei Lu, Yunrui Lian, Ziqing Chen, Yun Liu, Chenghuai Lin, Han Xue, Zicheng Zeng, Zekun Qi, Shaolin Zheng, Qing Luan, Jingbo Wang, Junliang Xing, He Wang, Li Yi arXiv*, 2026 project page / arXiv / code (LATENT) We propose LATENT, a system that Learns Athletic humanoid TEnnis skills from imperfect human motioN daTa.
	Collision-Free Humanoid Traversal in Cluttered Indoor Scenes Han Xue, Sikai Liang, Zhikai Zhang, Zicheng Zeng, Yun Liu, Yunrui Lian, Jilong Wang, Qingtao Liui, Xuesong Shi, Li Yi arxiv*, 2026 project page / arXiv / code (Click-and-Traverse) We propose Humanoid Potential Field (HumanoidPF) for collision-free traversal in cluttered indoor scenes with dexterous and versatile skills.
	Track Any Motions under Any Disturbances Zhikai Zhang, Jun Guo, Chao Chen, Jilong Wang, Chenghuai Lin, Yunrui Lian, Han Xue, Zhenrong Wang, Maoqi Liu, Jiangran Lyu, Huaping Liu, He Wang, Li Yi arXiv, 2025 project page / arXiv / code (OpenTrack) We present Any2Track, a foundational humanoid motion tracker to track any motions under any disturbances.
	Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space Zhikai Zhang, Chao Chen, Han Xue, Jilong Wang, Sikai Liang, Zongzhang Zhang, He Wang, Li Yi RA-L, 2025 LEAP Workshop @ CoRL*, 2025 (Spotlight) project page / arXiv / code (OpenWBT) We present Real-world-Ready Skill Space (R2S2), a skill space that encompasses and encodes various real-world-ready motor skills.
	GenN2N: Generative NeRF2NeRF Translation Xiangyue Liu, Han Xue, Kunming Luo, Ping TAN, Li Yi CVPR, 2024 project page / arXiv / code (GenN2N) GenN2N is a unified NeRF-to-NeRF translation framework for various NeRF translation tasks such as text-driven NeRF editing, colorization, super-resolution, inpainting, etc.

Thanks to Jon Barron for the template.