Tao Du 杜韬

Incoming Assistant Professor
Institute for Interdisciplinary Information Sciences (IIIS)
Tsinghua University
Email: taodu.eecs@gmail.com | Google Scholar | OpenReview

About Me

I am an incoming Assistant Professor at the Institute of Interdisciplinary Information Science (IIIS), Tsinghua University. My research combines physics simulation, machine learning, and numerical optimization techniques to solve real-world inverse dynamics problems. Some of my recent research topics are building differentiable simulation platforms for graphics and robotics research, developing computational design pipelines for real-world robots, and understanding simulation-to-reality transfer of dynamic systems.

Before joining Tsinghua, I was a Postdoctoral Associate at MIT CSAIL advised by Wojciech Matusik and Daniela Rus. I completed my Ph.D. in Computer Science (2021) at MIT, under the supervision of Wojciech Matusik. I obtained my Master's in Computer Science (2015) from Stanford University and my Bachelor's in Computer Software (2013) from Tsinghua University.

To prospective students: I am actively looking for students to work on topics in computer graphics, machine learning, and robotics. Students with relevant backgrounds in math, physics, and computer science are all welcome to contact me. Please feel free to drop me an email if you are interested.


08/2022: One paper is accepted to SIGGRAPH Asia 2022.
07/2022: Recognized by ICML 2022 as an Outstanding Reviewer.
07/2022: Two papers are accepted to IROS 2022.


(* indicates equal contributions)

Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models

Elvis Nava, John Z. Zhang, Mike Yan Michelis, Tao Du, Pingchuan Ma, Benjamin F. Grewe, Wojciech Matusik, Robert K. Katzschmann, ICML 2022

[Paper] [arXiv]

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact

Yifei Li, Tao Du, Kui Wu, Jie Xu, Wojciech Matusik. ACM Transactions on Graphics 2022 (SIGGRAPH 2022)

[Project] [arXiv]

RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation

Pingchuan Ma*, Tao Du*, Joshua B. Tenenbaum, Wojciech Matusik, Chuang Gan. ICLR 2022 (Oral)

[Project] [Paper]

Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics

Sizhe Li*, Zhiao Huang*, Tao Du, Hao Su, Joshua B. Tenenbaum, Chuang Gan. ICLR 2022 (Spotlight)

[Project] [Paper]

Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language

Mingyu Ding, Zhenfang Chen, Tao Du, Ping Luo, Joshua B. Tenenbaum, Chuang Gan. NeurIPS 2021

[Project] [Paper] [Code]

Advanced Soft Robot Modeling in ChainQueen

Andrew Spielberg, Tao Du, Yuanming Hu, Daniela Rus, Wojciech Matusik. Robotica 2021


DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation

Pingchuan Ma, Tao Du, John Z. Zhang, Kui Wu, Andrew Spielberg, Robert K. Katzschmann, Wojciech Matusik. ACM Transactions on Graphics 2021 (SIGGRAPH 2021)

[Project] [Paper] [arXiv] [Code]

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B. Tenenbaum, Chuang Gan. ICLR 2021 (Spotlight)

[Project] [Paper] [Code]

Efficient Continuous Pareto Exploration in Multi-Task Learning

Pingchuan Ma*, Tao Du*, Wojciech Matusik. ICML 2020

[Project] [Paper] [arXiv] [Code] [Talk] [Slides]

Learning-in-the-Loop Optimization: End-to-End Control and Co-Design of Soft Robots through Learned Deep Latent Representations

Andrew Spielberg, Allan Zhao, Tao Du, Yuanming Hu, Daniela Rus, Wojciech Matusik. NeurIPS 2019


Learning to Fly: Computational Controller Design for Hybrid UAVs with Reinforcement Learning

Jie Xu, Tao Du, Michael Foshey, Beichen Li, Bo Zhu, Adriana Schulz, Wojciech Matusik. ACM Transactions on Graphics 2019 (SIGGRAPH 2019)

[Project] [Paper] [Code]

Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains

Justin Solomon, Fernando de Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, Leonidas Guibas. ACM Transactions on Graphics 2015 (SIGGRAPH 2015)

[Paper] [Code]


Differentiable Simulation Methods for Robotic Agent Design

Ph.D. thesis

[Thesis] [Video]


The Power of Gradients in Inverse Dynamics Problems

A summary of our recent works on inverse dynamics problems.



Program Committee: PG
Journal paper reviewer: TOG, T-RO, RA-L
Conference paper reviewer: SIGGRAPH, SIGGRAPH Asia, PG, NeurIPS (Outstanding Reviewer), ICLR, ICML (Outstanding Reviewer), RSS, ICRA, IROS