Fatemeh Zargarbashi

Robotics, Character animation, Reinforcement learning

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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. Prior to that I recieved a B.SC. in Mechanical Engineering from Sharif Univeristy of Technology. I also achieved a Gold Medal and the Creativity Award at the International Olympiad in Astronomy and Astrophysics (IOAA), held in Indonesia in 2015.

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

Jun 25, 2026 Our paper, “Two2Four: Generative Quadruped Puppeteering from Human Motion”, has been accepted at SCA 2026! 🎉
Mar 01, 2026 Our paper, “VQ-Style: Disentangling Style and Content in Motion with Residual Quantized Representations” has been accepted to Eurographics 2026! 🎉 [Arxiv]
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

Latest posts

Selected publications

  1. Two2Four.png
    Two2Four: Generative Quadruped Puppeteering from Human Motion
    Fatemeh Zargarbashi, Zehong Qiu, Dhruv Agrawal, and 4 more authors
    ACM SIGGRAPH / Eurographics Symposium on Computer Animation (SCA), 2026
  2. vqStyle.png
    VQ-Style: Disentangling Style and Content in Motion with Residual Quantized Representations
    Fatemeh Zargarbashi, Dhruv Agrawal, Jakob Buhmann, and 3 more authors
    Computer Graphics Forum, Eurographics, 2026
  3. SwitchJustDance.png
    Switch-JustDance: Benchmarking Whole-Body Motion Tracking Controllers Using a Commercial Console Game
    Jeonghwan Kim, Wontaek Kim, Yidan Lu, and 8 more authors
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026
  4. 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
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
  5. 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
  6. 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 Annual Conference on Robot Learning (CoRL), 2024