Master's student
Johns Hopkins University
Robotics · Perception · Learning
Hi! I'm a Master's student in Mechanical Engineering at Johns Hopkins University, working on robotics and perception.
Before joining Johns Hopkins, I received my B.S. in Optoelectronic Information Science and Engineering from East China Normal University in 2024.
My research focuses on active perception and robot learning, with an emphasis on decision-making under partial observability. I study how robots can acquire task-relevant information and use it to guide perception, planning, and action.
I am currently working on projects involving vision-language-action (VLA) models, exploring how active perception can improve robotic manipulation.
Our paper Ergodic Trajectory Planning With Dynamic Sensor Footprints is now available in IEEE Transactions on Robotics Early Access.
IEEE Xplore →We released TRACE, our work on trajectory-level ergodic planning for active scene reconstruction.
Read the paper →* Equal contribution. 10 citations on Google Scholar. Updated Sep 06, 2026.
IEEE Transactions on Robotics (T-RO) · Early Access · 2026
Trajectory planning for information gathering with dynamic, resolution-varying sensor footprints, validated on a multi-drone system.
arXiv · 2026
Time-varying, footprint-aware ergodic planning for active Gaussian scene reconstruction, connecting informative camera trajectories with real robot deployment.
Advanced Electronic Materials · 2025
Neural-network potentials for modeling irradiation-induced defects in silicon carbide.
Journal of Applied Physics · 2025