Le Chen
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.

I am interested in building general agents and robots that can perform a wide range of tasks. My research falls at the intersection of robotics and reinforcement learning. I am now working on dexterous manipulation.

E-Mail / LinkedIn / Github

Research

Generalist World Model Pre-Training for Efficient Reinforcement Learning

Yi Zhao, Aidan Scannell, Yuxin Hou, Tianyu Cui, Le Chen, Dieter Büchler, Arno Solin, Juho Kannala, Joni Pajarinen

Preprint, 2025.

paper

RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands

Yi Zhao*, Le Chen*, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler

Conference on Robot Learning (CoRL), 2024
(*: equal contribution)

paper website dataset code video

Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion

Simon Guist, Jan Schneider, Hao Ma, Le Chen, Vincent Berenz, Julian Martus, Heiko Ott, Felix Grüninger, Michael Muehlebach, Jonathan Fiene, Bernhard Schölkopf, Dieter Büchler

Robotics: Science and Systems (RSS), 2024

paper website dataset hardware software

GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation

Quankai Gao, Qiangeng Xu, Zhe Cao, Ben Mildenhall, Wenchao Ma, Le Chen, Danhang Tang, Ulrich Neumann

Preprint, 2024.

paper website code

Identifying Policy Gradient Subspaces

Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel Haeufle, Bernhard Schölkopf, Dieter Büchler

International Conference on Learning Representations (ICLR), 2024

paper website code

LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry

Weirong Chen, Le Chen, Rui Wang, Marc Pollefeys

IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024

paper code website video poster

Leveraging Neural Radiance Fields for Uncertainty Aware Visual Localization

Le Chen, Weirong Chen, Rui Wang, Marc Pollefeys

IEEE International Conference on Robotics and Automation (ICRA), 2024

paper video

Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields

Soomin Lee*, Le Chen*, Jiahao Wang, Alexander Liniger, Suryansh Kumar, Fisher Yu

IEEE Robotics and Automation Letters (RA-L), 2022
IEEE International Conference on Robotics and Automation (ICRA), 2023
(*: equal contribution)

paper website video bibtex

Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning

Yunke Ao*, Le Chen*, Florian Tschopp, Michel Breyer, Andrei Cramariuc, Roland Siegwart

IEEE International Conference on Robotics and Automation (ICRA), 2022
(*: equal contribution)

paper poster supp video code bibtex

Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning

Le Chen*, Yunke Ao*, Florian Tschopp, Andrei Cramariuc, Michel Breyer, Jen Jen Chung, Roland Siegwart, Cesar Cadena

Conference on Robot Learning (CoRL), 2020
(*: equal contribution)

paper spotlight talk supp video code bibtex

Jiles-Atherton Based Hysteresis Identification of Shape Memory Alloy-Actuating Compliant Mechanism via Modified Particle Swarm Optimization Algorithm

Le Chen, Ying Feng, Rui Li, Xinkai Chen, Hui Jiang,

Complexity, vol. 2019.

paper bibtex

Projects

Transition From Model-Based to Model-Free Actor-Critic Reinforcement Learning

Le Chen, Yunke Ao, Kaiyue Shen, Zheyu Ye

Course Project in Deep Learning, 2020

report code

Leveraging Pixel Correspondences for Sparse-to-Dense Feature-Metric Localization

Le Chen, Lixin Xue, Zimeng Jiang

Course Project in 3D Vision, 2020

report code