Yufeng Li 李雨峰

Ph.D. Student @ Shanghai Jiao Tong University

I am a Ph.D. student at Shanghai Jiao Tong University, advised by Prof. Junchi Yan. I am also jointly trained at Beijing Zhongguancun College, advised by Researcher Kai Chen.

My research focuses on embodied intelligence for precise and safety-critical robotic systems. I am interested in scientific robotics, dexterous manipulation, vision-language-action models, safe reinforcement learning, optimal transport, and generative policy learning.

Recent projects study how robots can operate in chemical-laboratory environments, how VLA models can specialize task-relevant action factors, and how optimal-flow views can support safer reinforcement learning.

Portrait of Yufeng Li

Updates

[Jun. 2026] SafeLab, ICML 2026.
[May 2026] GuidedVLA, RSS 2026.
[Apr. 2025] Optimal Flow Transport and its Entropic Regularization, ICLR 2025.
[Oct. 2024] REFRAME, ECCV 2024.

Selected Publications

Optimal Flow Transport figure

Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction

L. Shi, Y. Li, K. Zeng, Y. Tu, J. Yan, et al.

International Conference on Learning Representations (ICLR), 2025

A matrix-iterative optimal transport algorithm for satisfying node and edge flow balance constraints in graph-structured problems.

GuidedVLA figure

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization

X. Jia, B. Yang, Z. Ge, X. Nie, Y. Zhou, C. Fan, Y. Li, Y. Chai, C. Jing, Z. Liang, Q. Bu, H. Cao, C. Wu, Q. Li, Z. Yang, C. Zhang, H. Li, Z. Wu, J. Yan, Y.-G. Jiang

Robotics: Science and Systems (RSS), 2026

Decouples object pointing, spatial geometry, and timing skill factors by specializing action-decoder attention heads.

REFRAME rendering comparison figure

REFRAME: Reflective Surface Real-Time Rendering for Mobile Devices

C. Ji, Y. Li, Y. Liao, et al.

European Conference on Computer Vision (ECCV), 2024

Real-time novel-view synthesis pipeline for reflective surfaces on mobile devices.

WT-YOLO architecture figure

Efficient Packaging Line Object Counting by Cross-frame Association with Wavelet Convolutions and Trajectory Compensation

L. Wei, Y. Zhu, Y. Li, M. Qian, X. Zuo, B. Chen, S. Liang, Z. Lin, J. Yan, et al.

IEEE Access, 2025

Wavelet-convolution enhanced detection and cross-frame association for packaging line object counting.

Additional Manuscripts

  • GEARS: Seeing Geometry, Diffusing Actions for Zero-Shot Sim-to-Real Dexterous Manipulation F. Bai, T. Chou, Y. Li, Y. Li, Y. Wang, Y. Mao, H. Zhang, Y. Wang, R. Zhu, Y. Wen, Y. Yang, Y. Chen, et al. Submitted to ECCV, 2026.
  • SafeTransport: A Unified Capacity-Flow View of Safe Reinforcement Learning Y. Li, F. Bai, T. Chou, Q. Li, J. Gao, J. Yan Submitted to NeurIPS, 2026.
  • Rsync: Reward-Manifold Driven Adaptive Synchronization for Sample-Efficient Real-World Reinforcement Learning Y. Cai, F. Bai, T. Yu, Y. Pu, Y. Mao, Y. Wang, T. Chou, Y. Li, Y. Li, Y. Yang, H. Zhang, M. Li, Y. Chen, et al. Submitted to NeurIPS, 2026.
  • Remembering What Matters: From Markovian to Subtask-Causal Memory in VLA Policies Peishuo Wang, Fengshuo Bai, Yufeng Li, Tawei Chou, Yinda Xu, Ying Wen, Yaodong Yang, Chen Gao, Zhenzhe Zheng, Fan Wu Submitted to NeurIPS, 2026.

Experience


Education and Honors


Selected Project

Local-first AI workflow system

ShrimpFlow

A programmer workflow system that observes terminal, git, and AI-agent interaction traces, models a developer's workflow and cognitive preferences, and exports executable behavior specifications such as ClawProfile / CLAUDE.md for personalized AI coding agents.

  • Shadow layer: terminal, git, agent-session, and environment event collection.
  • Brain layer: workflow, preference, decision, and temporal pattern modeling.
  • Autopilot layer: portable behavior specs for downstream coding agents.