Runhan Huang

I am an undergraduate student from Tsinghua University, Yao Class. At Tsinghua University, I am fortunately advised by Prof. Hang Zhao in MARS Lab. At Harvard's Kempner AI institute, I am a visiting researcher advised by Prof. Yilun Du. I also spent time at Shanghai Qizhi Institute.

I am currently seeking for a PhD position for Fall 2026. Feel free to reach out via email at runhanhuang2004(at)gmail.com!

Email  /  CV  /  Scholar  /  Github

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Recent News

  • One paper accepted by ICRA 2025! Check out the website and code.
  • My personal website is out!

Research

Currently, my research interest includes reinforcement learning, robotics and generative models. I am also open to explore other research topics. Some papers are highlighted.

MoELoco: Mixture of Experts for Multitask Locomotion
Runhan Huang*, Shaoting Zhu*, Yilun Du, Hang Zhao,
In Submission
project page / video / arXiv

MoELoco introduces a multitask locomotion framework that employs a mixture-of-experts strategy to enhance reinforcement learning across diverse tasks while leveraging compositionality to generate new skills.

VR-Robo: A Real-to-Sim-to-Real Framework for Visual Robot Navigation and Locomotion
Shaoting Zhu*, Linzhan Mou*, Derun Li, Baijun Ye, Runhan Huang, Hang Zhao,
In Submission
project page / video / arXiv

VR-Robo introduces a digital twin framework using 3D Gaussian Splatting for photorealistic simulation, enabling RGB-based sim-to-real transfer for robot navigation and locomotion.

Robust Robot Walker: Learning Agile Locomotion over Tiny Traps
Shaoting Zhu, Runhan Huang, Linzhan Mou, Hang Zhao,
ICRA, 2025
project page / video / arXiv / code

We propose a proprioception-only, two-stage training framework with goal command and a dedicated tiny trap benchmark, enabling quadruped robots to robustly traverse small obstacles.


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