Zeju Li

Email: zeju (dot) li (dot) cs [at] gmail (dot) com

I'm an undergraduate student at Zhejiang University, pursuing a bachelor's degree in Computer Science and Technology (expected to graduate in Jun 2027).

Fascinated by movies such as I, Robot, Real Steel, and Big Hero 6, I am passionate about developing truly intelligent robots capable of general-purpose autonomy in human-centric environments.

I am currently a research intern at MLL-Lab, Northwestern University, where I am fortunate enough to be advised by Prof. Manling Li and Prof. Ruohan Zhang. Previously, I had the privilege of working as a research assistant at the State Key Lab of CAD&CG, Zhejiang University, under the guidance of Prof. Hao Chen and Prof. Chunhua Shen.

I am seeking Ph.D. opportunities for Fall 2027 and would be glad to connect about research and potential collaborations.

Google Scholar CV (Sep 2026) GitHub
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News

Sep 5, 2026 STAIR is accepted to CoRL-2026! 🎉

Mar 31, 2026 AGILE is accepted to SIGGRAPH-2026!

Feb 21, 2026 StaMo is accepted to CVPR-2026 as an Highlight Presentation!

Nov 08, 2025 ODYSSEY is accepted to AAAI-2026 as an Oral Presentation!

Research

* Equal contributions, † Corresponding author

	Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments Mingyu Liu^, Zeju Li^, Jiuhe Shu, Hanqing Wang, Yuhao Chao, Hao Chen^†, Chunhua Shen^† [project page] [arXiv] CoRL, 2026 Robust robot learning needs corrective alignment dynamics, not just fluent expert trajectories.
	StaMo: Unsupervised Learning of Generalizable Robot Motion from Compact State Representation Mingyu Liu^, Jiuhe Shu^, Hui Chen, Zeju Li, Canyu Zhao, Jiange Yang, Shenyuan Gao, Hao Chen^†, Chunhua Shen^† [project page] [arXiv] CVPR, 2026 [Highlight Presentation, Top 3.1%] Compact state representations for efficient world modeling and action learning.
	ODYSSEY: Open-World Quadrupeds Exploration and Manipulation for Long-Horizon Tasks Kaijun Wang^, Liqin Lu^, Mingyu Liu, Jianuo Jiang, Zeju Li, Bolin Zhang, Wancai Zheng, Xinyi Yu^†, Hao Chen^†, Chunhua Shen^† [project page] [arXiv] AAAI, 2026 [Oral Presentation, Top 3.5%] Language-guided long-horizon mobile manipulation with a benchmark.
	AGILE: Hand-Object Interaction Reconstruction from Video via Agentic Generation Jin-Chuan Shi^, Binhong Ye^, Tao Liu, Junzhe He, Yangjinhui Xu, Xiaoyang Liu, Zeju Li, Hao Chen^†, Chunhua Shen^† [project page] [arXiv] SIGGRAPH, 2026 [Conference Track] Reconstruct simulation-ready hand-object interaction from monocular video via agentic generation and robust pose tracking.