Resume
Academic Achievements
- Paper 'Accelerating Visual-Policy Learning through Parallel Differentiable Simulation' accepted to NeurIPS 2025 as a Spotlight paper; preprint 'Is Bellman Equation Enough for Learning Control?'
Research Experience
- Worked with Professors Michael Posa and Pratik Chaudhari at the University of Pennsylvania.
Education
- Bachelor's degree from Ningbo University; Master's degree from the University of Pennsylvania, where he received the Outstanding Academic Award and worked with Professors Michael Posa and Pratik Chaudhari; Ph.D. student in the Department of Mechanical Engineering at Yale University, advised by Professor Ian Abraham.
Background
- Broadly interested in robotics, machine learning, control theory, and optimization. Currently, the research focuses on developing computationally efficient algorithms for robot learning.
Miscellany
- Enjoys playing computer games, DIY projects, and cooking outside of research.