Yong-Lu Li
Scholar

Yong-Lu Li

Google Scholar ID: UExAaVgAAAAJ
Associate Professor, Shanghai Jiao Tong University/Shanghai Innovation Institute
Physical ReasoningRoboticsComputer VisionMachine LearningEmbodied AI
Citations & Impact
All-time
Citations
3,020
 
H-index
21
 
i10-index
33
 
Publications
20
 
Co-authors
19
list available
Resume (English only)
Academic Achievements
  • - ICRA 2025 Best Paper Award (HRI, sole corresponding author)
  • - AI100 Young Pioneers (MIT Review)
  • - Baidu Scholarship
  • - WAIC Yunfan Award (twice)
  • - Shanghai Overseas High-Level Talent
  • - Wu Wenjun AI Science and Technology Award for Excellent Doctoral Dissertation
  • - Outstanding Reviewer of NeurIPS’20/21
  • - Area Chair for ICLR 2026
  • - Lecturer for the 'Computer Vision' course at the ACM Honor Class of SJTU
  • - Member of VALSE EACC
  • - Deputy Secretary-General of the EAI Committee under the Chinese Association for AI
  • - Multiple papers published in SIGGRAPH Asia 2025, CoRL 2025, ICCV 2025, IROS 2025, etc.
Research Experience
  • - Tenure-Track Associate Professor at Shanghai Jiao Tong University
  • - PI of the RHOS Lab
  • - Member of the Machine Vision and Intelligence Group, working closely with Prof. Cewu Lu
  • - Previously collaborated with Prof. Chi Keung Tang and Prof. Yu-Wing Tai at the Hong Kong University of Science and Technology (2021-2022)
Education
  • - Ph.D. (2017-2021): Computer Science, Shanghai Jiao Tong University, supervised by Prof. Cewu Lu
  • - Work and study (2014-2017): Institute of Automation, Chinese Academy of Sciences, supervised by Prof. Yiping Yang and A/Prof. Yinghao Cai
  • - Collaboration (2021-2022): Hong Kong University of Science and Technology, closely worked with IEEE Fellow Prof. Chi Keung Tang and Prof. Yu-Wing Tai
Background
  • - Research Interests: Physical Reasoning, Embodied AI, Human Activity Understanding
  • - Position: Tenure-Track Associate Professor at Shanghai Jiao Tong University, PI of the RHOS Lab
  • - Introduction: Focuses on building a reasoning-driven system that enables intelligent agents to perceive, reason, and interact with the physical world. Open-source projects have garnered over 13,000 stars on GitHub.
Miscellany
  • - Personal interests not detailed