Tengbo Yu

Tengbo Yu | 于腾博

I am a first-year Ph.D. student at Peking University, supervised by Prof. Hangxin Liu. I am currently an intern at Delta Intelligence. My research focuses on Embodied AI, I am working on Robotic Foundation Models that help robots learn diverse tasks in the real world.

Previously, I interned at BIGAI. I received my master's degree from Tsinghua University Shenzhen International Graduate School, and my bachelor's degree from the School of Computer Science and Technology at Shandong University in 2023.

Email / Github / Scholar / LinkedIn

Publications and Preprints

* indicates equal contribution

	PRISM: Precision and contact-rich Real-world Industrial Skill Dataset with Multimodal Sensing Tengbo Yu, Jiahao Wu, Hanning Wang, Rui Chen, Chuanhou Liu, Chuang Sun, Hangxin Liu^† IROS 2026 [Project Page] [Paper] We proposed PRISM, a large-scale multimodal dataset for contact-rich real-world industrial manipulation..
	CoT4AD: A Vision-Language-Action Model with Explicit Chain-of-Thought Reasoning for Autonomous Driving Zhaohui Wang, Tengbo Yu, Hao Tang ACM MM 2026 [Project Page] We proposed CoT4AD, a vision-language-action model with explicit chain-of-thought reasoning for autonomous driving.
	ManiGaussian++: Dynamic Gaussian Splatting for Multi-task Bimanual Manipulation Tengbo Yu, Guanxing Lu, Zaijia Yang, Haoyuan Deng, Season Si Chen, Jiwen Lu, Wenbo Ding, Guoqiang Hu, Yansong Tang^†, Ziwei Wang IROS 2025* [arXiv] [Code] We proposed ManiGaussian++, a novel framework that addresses the challenges of multi-task bimanual manipulation through hierarchical Gaussian world modeling.
	AnyBimanual: Transferring Unimanual Policy for General Bimanual Manipulation Guanxing Lu, Tengbo Yu, Haoyuan Deng, Season Si Chen, Yansong Tang^†, Ziwei Wang ICCV 2025 [Project Page] [Code] We introduced AnyBimanual, a framework designed to transfer pre-trained unimanual manipulation policies to multi-task bimanual manipulation with few bimanual demonstrations.

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