Fatemeh Zargarbashi

Robotics, Character animation, Reinforcement learning

prof_pic.jpg

PhD Candidate,

ETH Zurich,

Disney research | Studios

Hi! I’m Fatemeh.

I am a Ph.D. candidate in Computer Science jointly at ETH Zurich (Computational Robotics Lab) and Disney research Studios. My research lies in bridging the gap between robotics and character animation by investigating how to develop natural motions on legged robots and how to control physics-based animated characters. I am also interested in developing reinforcement learning algorithms for character control, legged locomotion, and motion generation.

I received my M.Sc. in Mechanical Engineering, Control from Sharif University of Technology, Tehran, Iran. During my master thesis I worked on the development and control of an over-actuated quadcopter for agile maneuvers.

In my free time, I like cycling, swimming and reading poetry. I am also an amateur astronomer and I like to go stargazing :telescope: whenever I have the chance. Recently, I have started exploring night sky photography :camera:!

News

Oct 02, 2025 I had the opportunity to be at CoRL and Humanoids conferences to promote some of our recent works. It’s quite an exciting time to be a roboticist! Every week a new company unveils their robot hardware, and every day you see a new interesting idea in the academic papers. Can’t imagine how our robotic world will look like in 10 years, but it’s going to be exciting! See video
Jul 05, 2025 We hosted a booth in the annual ETH RobotX innovation day, with a couple of demos of our research and robots! see post on linkedin
Sep 05, 2024 I’m thrilled to share that our paper, “RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards”, has been accepted at CoRL 2024! 🎉 [arxiv], [youtube]

Latest posts

Jan 06, 2026 Generative Motion Synthesis Lecture
Jul 08, 2025 Try DeepMimic in Isaacgym with our assignment

Selected publications

  1. WbMpcLocoman.png
    Whole-Body Inverse Dynamics MPC for Legged Loco-Manipulation
    Lukas Molnar, Jin Cheng, Gabriele Fadini, and 3 more authors
    IEEE Robotics and Automation Letters, 2025
  2. Apex.gif
    APEX: Action Priors Enable Efficient Exploration for Robust Motion Tracking on Legged Robots
    Shivam Sood, Laukik Nakhwa, Sun Ge, and 7 more authors
    arXiv preprint arXiv:2511.09091, 2025
  3. SteerableAnimal.png
    Learning Steerable Imitation Controllers from Unstructured Animal Motions
    Dongho Kang, Jin Cheng, Fatemeh Zargarbashi, and 3 more authors
    arXiv preprint arXiv:2507.00677, 2025
  4. RobotKeyframing.png
    RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards
    Fatemeh Zargarbashi, Jin Cheng, Dongho Kang, and 2 more authors
    8th Conference on Robot Learning (CoRL), 2024
  5. MetaLoco.png
    MetaLoco: Universal Quadrupedal Locomotion with Meta-Reinforcement Learning and Motion Imitation
    Fatemeh Zargarbashi, Fabrizio Di Giuro, Jin Cheng, and 3 more authors
    arXiv preprint arXiv:2407.17502, 2024
  6. RL_MBOC.png
    Rl+ model-based control: Using on-demand optimal control to learn versatile legged locomotion
    Dongho Kang, Jin Cheng, Miguel Zamora, and 2 more authors
    IEEE Robotics and Automation Letters, 2023