Robot Learning · Manipulation
Ph.D. Student in Electrical and Computer Engineering at the National University of Singapore
I work on robot learning and robotic manipulation, with an emphasis on reinforcement learning, vision-language-action models, simulation, and real-robot systems.
I received my M.Sc. in Robotics from the National University of Singapore and my B.Eng. in Robotics Engineering from the University of Electronic Science and Technology of China.
Goal: Build reliable robots that can learn, adapt, and improve through real-world interaction.
Conference on Robot Learning (CoRL), 2026
A lightweight visual comparator that turns one successful demonstration into a dense reward while suppressing uncertain progress estimates that may cause reward hacking.
Conference on Robot Learning (CoRL), 2026
A closed-loop real-to-sim-to-real framework that reconstructs cloth state from RGB observations and refines nominal actions through FLASH rollouts and prior-guided MPPI.
Built VLA data-collection and real-robot rollout infrastructure, reproduced real-world RL baselines, integrated human intervention, and evaluated dense progress rewards on dual-arm manipulation tasks.
Designed STM32 control boards, sensor and IMU modules, CAN/UART networks, a compact FOC motor driver, and embedded firmware for the national-champion elephant and bunny robots.