Yunsheng Tian

Yunsheng Tian

Applied Scientist @ Amazon FAR

yunsheng@mit.edu

I am an Applied Scientist at Amazon FAR (Frontier AI & Robotics). Prior to that, I earned my PhD degree from MIT EECS and my bachelor’s degree from Nankai University, and have interned at MIT-IBM Watson AI Lab, Autodesk Research, HKU, and MSR Asia.

I am currently working towards building human-level robotic foundation models. My PhD research focuses on scalable robotic assembly of general objects, involving task and motion planning, reinforcement learning, physics-based simulation, geometry processing, and precise manipulation.

Outside research, I am a picky foodie spoiled by my wife, who knows how to cook everything.

Interests

  • 🤖

    Robotics

    Planning, Manipulation, RL

  • 🧠

    Machine Learning

    Foundation Models, BayesOpt

  • 🎨

    Computer Graphics

    Physics Simulation, CAD

Education

  • PhD in Computer Science, 2019 - 2025

    Massachusetts Institute of Technology

  • MS in Computer Science, 2019 - 2021

    Massachusetts Institute of Technology

  • BEng in Software Engineering, 2015 - 2019

    Nankai University

Publication

Scalable Assembly of General Objects

Scalable Assembly of General Objects 🎓

Yunsheng Tian
PhD Thesis 2025
A scalable system towards fully automated and flexible robotic assembly that generalizes over diverse geometries.
PDF
Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning

Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning 🤖

CoRL 2025 (Best Paper Award)
Generalizable, long-horizon, and contact-rich multi-part object assembly by dual-arm robots in the real world.
PDF Project Video Talk
A multimodal robotic platform for multi-element electrocatalyst discovery

A multimodal robotic platform for multi-element electrocatalyst discovery 🧠 🤖

Zhen Zhang, Zhichu Ren, Chia-Wei Hsu, Weibin Chen, Zhang-Wei Hong, Chi-Feng Lee, Aubrey Penn, Hongbin Xu, Daniel J. Zheng, Shuhan Miao, Yimeng Huang, Yifan Gao, Weiyin Chen, Hugh Smith, Yaoshen Niu, Yunsheng Tian, Ying-Rui Lu, Yu-Cheng Shao, Sipei Li, Hsiao-Tsu Wang, Iwnetim I. Abate, Pulkit Agrawal, Yang Shao-Horn, Ju Li
Nature 2025
NeurIPS 2023 RealML Workshop (Best Student Paper Award)
Accelerated scientific discovery through large multimodal models, Bayesian optimization, and autonomous robots.
PDF Video
ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility

ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility 🤖 🧠

ICRA 2024
MIT MIMO Symposium 2023 (Zetta Prize, Best Application of AI in Industry)
Automated robotic assembly plan generation for complex and general-shaped assemblies.
PDF Code Dataset Project Poster Slides Video
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints 🧠

ICML 2024
Efficient global optimizer for physical designs with unknown constraints.
PDF Code Poster
AutODEx: Automated Optimal Design of Experiments Platform with Data- and Time-Efficient Multi-Objective Optimization

AutODEx: Automated Optimal Design of Experiments Platform with Data- and Time-Efficient Multi-Objective Optimization 🧠

NeurIPS 2023 RealML Workshop
Easy-to-use experimental design platform based on asynchronous multi-objective BO.
PDF Project Poster Video
Assemble Them All: Physics-Based Planning for Generalizable Assembly by Disassembly

Assemble Them All: Physics-Based Planning for Generalizable Assembly by Disassembly 🤖 🎨

ACM TOG / SIGGRAPH Asia 2022 (Journal Track)
Physics makes motion planning for complex assemblies simple, fast, and generalizable.
PDF Code Dataset Project Video Talk MIT News
JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints

JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints 🧠 🎨

CVPR 2022
Learning to assemble on a big CAD assembly dataset approaching human-level accuracy.
PDF Code Dataset
Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots

Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots 🤖

NeurIPS 2021
The first and largest benchmark for evolving soft robot morphology.
PDF Code Project Poster Video MIT News Wired IEEE Spectrum
Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations

Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations 🧠

Yunsheng Tian*, Mina Konaković Luković*, Wojciech Matusik (* indicates equal contribution)
NeurIPS 2020
Efficient multi-objective optimizer for expensive black-box functions.
PDF Code Poster Video Supplementary
Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control

Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control 🧠 🤖

ICML 2020
Efficient multi-objective RL for discovering all Pareto-optimal policies.
PDF Code Project Video Talk Supplementary
Fluid Directed Rigid Body Control using Deep Reinforcement Learning

Fluid Directed Rigid Body Control using Deep Reinforcement Learning 🤖 🎨

Yunsheng Tian*, Pingchuan Ma*, Zherong Pan, Bo Ren, Dinesh Manocha (* indicates equal contribution)
ACM TOG / SIGGRAPH 2018
Deep RL can control high-dimensional fluid-rigid coupling dynamics.
PDF Project Video DOI Talk

Project

Genesis: A Generative and Universal Physics Engine for Robotics and Beyond

Genesis: A Generative and Universal Physics Engine for Robotics and Beyond 🤖

Genesis Team
Open-Source Code
A universal physics engine towards fully automated data generation for robotics and beyond.
Code Project
Autonomous Robotic Assembly of a Skateboard Truck

Autonomous Robotic Assembly of a Skateboard Truck 🤖

Yotto Koga, Hui Li, Xiang Zhang, Yunsheng Tian, Adam Arnold, James Emerick, Nic Carey, Srinidhi Srinivas, Nick Cote, Michael Koehle, Stefanie Pender, Noa Kaplan, Annabella Macaluso, Gadiel Sznaier Camps, Ozguc Capunaman, Gabrielle Patin, Hans Kellner, Sachin Chitta
Autodesk Research Demo
Autonomous assembly of a mechanical skateboard truck with a flexible robotic system.
Project Video

Service


Conference Reviewer: SIGGRAPH/SIGGRAPH Asia, CoRL, ICRA, IROS, ICLR, ICML, NeurIPS, AISTATS

Journal Reviewer: RA-L, TVCG, TEVC, Soft Computing, TMLR

Workshop Organizer: CoRL 2024 Robotic Assembly Workshop

Invited Talks:

  • [2024/07] DigitalFUTURES Workshop: “Towards Generalizable and Adaptive Robotic Assembly of Industrial and Everyday Objects”
  • [2023/11] Tsinghua University IIIS Seminar: “Towards Automated Planning and Execution for Generalizable and Complex Robotic Assembly”
  • [2023/08] Autodesk Research Connections: “Physics-Based Planning for Automated Robotic Assembly”
  • [2023/03] MIT Graphics Seminar: “Physics-Based Planning for Automating Contact-Rich Assembly”
  • [2021/04] MIT CSAIL Alliances Tech Workshop: “Automated Multi-Objective Optimal Experiment Design Platform”
  • [2020/11] Lam Research Seminar: “Multi-Objective Bayesian Optimization for Adaptive Experimental Design”

Teaching and Mentoring:

  • [Fall 2023] Teaching Assistant for MIT EECS Advanced Computer Graphics/Computational Design and Fabrication
  • [Fall 2020 - Present] Research Mentor of 8 students participating in MIT UROP (Undergraduate Research Opportunities Program)