Scholar
Licheng Wen
Google Scholar ID: RNnjXTkAAAAJ
Shanghai AI Laboratory
Citations & Impact
Citations
1,934
H-index
14
i10-index
18
Publications
20
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving' accepted by ICCV 2025; Paper 'Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving' accepted by NeurIPS 2024; Paper 'LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving' accepted by IV 2024; Paper 'DiLu🐴: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models' accepted by ICLR 2024; Paper 'How drivers perform under different scenarios: Ability-related driving style extraction for large-scale dataset' published on Journal of Accident Analysis & Prevention.
Research Experience
- Currently a researcher at the Shanghai AI Laboratory, closely collaborating with the Shanghai Institute of Innovation. Prior work centered on addressing complex interaction challenges in autonomous driving.
Education
- Received a bachelor's degree from Zhejiang University in 2019; Obtained an M.Sc. degree from Zhejiang University in 2022, where he was a member of the APRIL Lab, advised by Dr. Yong Liu.
Background
- Research interests include AI Agents, Multimodal Foundation Models, Multi-Agent System, and Autonomous Driving. Focuses on enabling AI agents to operate efficiently in practical and valuable scenarios, with an emphasis on allowing foundation models to learn and improve during run-time rather than solely at design-time.
Miscellany
- Passionate about the future of artificial general intelligence (AGI) and excited to contribute to these rapidly advancing fields.
