Scholar
Chen Tang
Google Scholar ID: x78TL58AAAAJ
Incoming Assistant Professor in New Mobility, UCLA
Citations & Impact
Citations
922
H-index
16
i10-index
22
Publications
20
Co-authors
78
list available
Publications
Resume (English only)
Academic Achievements
- Three papers accepted for CoRL 2025: SocialNav-SUB, ComposableNav, and MEReQ
- Paper accepted for ICML 2025: WOMD-Reasoning: A Large-Scale Dataset and Benchmark for Interaction and Intention Reasoning in Driving
- Paper accepted for ICLR 2025: Residual-MPPI: Online Policy Customization for Continuous Control
- Paper accepted for ECCV 2024: Optimizing diffusion models for joint trajectory prediction and controllable generation
- Papers accepted for IROS 2024: Pre-training on synthetic driving data for trajectory prediction and Skill-Critic: Refining learned skills for hierarchical reinforcement learning
- Paper accepted for IEEE Transactions on Control Systems Technology (T-CST): Active exploration in iterative gaussian process regression for uncertainty modeling in autonomous racing
- Paper accepted for RA-L: Learning online belief prediction for efficient POMDP planning in autonomous driving
- Received ASME DSCD Rising Star Awards in 2022
- Selected as an RSS Pioneer in 2023
Research Experience
- Assistant Professor in the Department of Civil and Environmental Engineering at UCLA, part of the New Mobility program of UCLA ITS. Formerly a Postdoctoral Fellow in Computer Science at UT Austin, working in the Learning Agents Research Group (LARG), advised by Prof. Peter Stone. Also a former Postdoctoral Scholar in Mechanical Engineering at UC Berkeley, working in the Mechanical Systems Control (MSC) Lab, advised by Prof. Masayoshi Tomizuka.
Education
- Ph.D. in Mechanical Engineering at UC Berkeley
- Bachelor's degree in Mechanical Engineering from the Hong Kong University of Science and Technology (HKUST)
- Postdoctoral Fellow in Computer Science at UT Austin, advised by Prof. Peter Stone
- Postdoctoral Scholar in Mechanical Engineering at UC Berkeley, advised by Prof. Masayoshi Tomizuka
Background
- Research interest lies at the intersection of control, robotics, and learning. Aims to develop embodied AI agents operating in human-centered environments. Dedicated to exploring principled approaches to integrate data-driven approaches (e.g., deep learning, generative models, reinforcement learning, and imitation learning) with control theory, explainable AI, and causality. Past and current research focused on applications in autonomous driving and robot navigation. Long-term research vision is to facilitate trustworthy and human-centered autonomy, aiming to expedite their integration into everyday life to yield substantial societal benefits.
Miscellany
- Recruiting PhD students for Fall 2026 to work on autonomous driving and robotics. Looking for postdocs, master's, and undergraduate students to join the lab.
