Shuo Sha

ss7050@columbia.edu

I'm an undergraduate student in Applied Mathematics and Computer Science at Columbia University, working in the RoboPIL Lab advised by Prof. Yunzhu Li. I'm fortunate to receive mentorship from Prof. Antonio Loquercio and Prof. Brian Plancher.

My research interests lie in the intersection of robotics, machine learning, and perception, with the aim of equipping physical agents with more robust, capable, and efficient skillsets to accomplish tasks and interact with the open world.

If you would like to collaborate, feel free to reach out!

CV / LinkedIn / GitHub / Twitter

Research

Efficient and Reliable Teleoperation through Real-to-Sim-to-Real and Shared Autonomy

Shuo Sha, Yixuan Wang, Binghao Huang, Antonio Loquercio, Yunzhu Li

(under review)
Real-to-Sim Robot Policy Evaluation with Gaussian Splatting Simulation of Soft-Body Interactions

Kaifeng Zhang*, Shuo Sha*, Hanxiao Jiang, Matt Loper, Jay Song, Zhuo Xu, Xiaochen Hu, Changxi Zheng, Yunzhu Li

ICRA 2026, [website], [paper], [code]
TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation

Shuo Sha, Anupam Bhakta, Zhenyuan Jiang, Kevin Qiu, Ishaan Mahajan, Gabriel Bravo, Brian Plancher

ICRA 2026, [paper], [code]
Analysis of 2D Maxwell's Equations in a Time-Harmonic Regime

Shuo Sha

Journal of Mathematics Research 2023, [paper]

Research

Efficient and Reliable Teleoperation through Real-to-Sim-to-Real and Shared Autonomy

Real-to-Sim Robot Policy Evaluation with Gaussian Splatting Simulation of Soft-Body Interactions

TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation

Analysis of 2D Maxwell's Equations in a Time-Harmonic Regime