Portrait
Junpeng Gao
PhD Student
Carnegie Mellon University
About Me

Hello, I am a PhD student advised by Prof. Andrew Spielberg in the Computational Invention Lab at CMU ECE. Previously, I earned my Master's degree in Computational Science and Engineering from ETH Zurich and my Bachelor's in Physics from ShanghaiTech University. My research interests lie in computational design, robotics, physics simulation and geometry processing.

During my master study, I worked on modeling soft robots with Mike Y. Michelis and Prof. Andrew Spielberg. I wrote my master thesis at Interactive Geometry Lab supervised by Prof. Olga Sorkine-Hornung. I was also an open-source contributer in Julia community before and implemented some high-performance numerical ODE solvers.

In my spare time, I enjoyed board games, manga and anime. I also had a great time doing Kondi when I was in Zurich.
Education
  • Carnegie Mellon University
    Carnegie Mellon University
    Electrical and Computer Engineering
    Ph.D. Student
    2025 - present
  • ETH Zurich
    ETH Zurich
    M.Sc. in Computational Science and Engineering
  • ShanghaiTech University
    ShanghaiTech University
    B.S. in Physics
Honors & Awards
  • IEEE RA-L Best Paper Award
    2024
  • Julia Community News
    2021
News
2025
Our paper received the RA-L Best Paper Award as one of only five papers for the year 2024 from among more than 1,500 papers published in RA-L during 2024!
Jan 13
2024
Our paper Sim-to-Real of Soft Robots with Learned Residual Physics has been accepted by RA-L. Check the project page
Jul 24
2021
My first open source contribution of three ODE solvers has been merged! Check the community news
May 24
Selected Publications (view all )
Sim-to-Real of Soft Robots with Learned Residual Physics
Sim-to-Real of Soft Robots with Learned Residual Physics

Junpeng Gao, Mike Y. Michelis, Andrew Spielberg, Robert K. Katzschmann

IEEE Robotics and Automation Letters (RA-L) 2024 Best Paper Award 2024

Our paper on sim-to-real transfer of soft robots using learned residual physics was accepted by RA-L and received the Best Paper Award as one of only five papers for the year 2024 from among more than 1,500 papers published in RA-L during 2024.

Sim-to-Real of Soft Robots with Learned Residual Physics

Junpeng Gao, Mike Y. Michelis, Andrew Spielberg, Robert K. Katzschmann

IEEE Robotics and Automation Letters (RA-L) 2024 Best Paper Award 2024

Our paper on sim-to-real transfer of soft robots using learned residual physics was accepted by RA-L and received the Best Paper Award as one of only five papers for the year 2024 from among more than 1,500 papers published in RA-L during 2024.

All publications