| CARVIEW |
Picture taken in Sagrada Familia
陳樂
I am a Computer Science PhD student at the Empirical Inference department of Max Planck Institute for Intelligent Systems and ETH Zurich, advised by Prof. Bernhard Schölkopf and Prof. Dieter Büchler. Previously, I obtained my M.S. in Electrical Engineering and Information Technology at ETH Zurich. I also spent time at Microsoft Mixed Reality & AI Lab in Zurich, Tencent AI Lab and Tencent Robotics X Lab.
My research focuses on building general agents and robots that can robustly perform a wide range of tasks. I am currently working on (1) dexterous manipulation with tactile sensing and (2) safe, compositional adaptation of foundation behavior models.
Research
Dexterous Robotic Piano Playing at Scale
Under Review, 2025
(*: equal contribution)
Efficient Reinforcement Learning by Guiding Generalist World Models with Non-Curated Data
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands
(*: equal contribution)
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion
GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation
Identifying Policy Gradient Subspaces
LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry
Leveraging Neural Radiance Fields for Uncertainty Aware Visual Localization
Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields
IEEE International Conference on Robotics and Automation (ICRA), 2023
(*: equal contribution)
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
(*: equal contribution)
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
(*: equal contribution)
Projects
Transition From Model-Based to Model-Free Actor-Critic Reinforcement Learning
