Yunsheng Tian

Yunsheng Tian

Member of Technical Staff @ Amazon FAR

yunsheng [at] mit [dot] edu

I am a Member of Technical Staff 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 🎓

PhD Thesis
A scalable system towards fully automated and flexible robotic assembly that generalizes over diverse geometries.
NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception

NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception 🤖

RSS 2026 (Best System Paper Award)
A neural actuator model for low-cost servo-driven robot platforms.
A multimodal robotic platform for multi-element electrocatalyst discovery

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

Nature 2025
NeurIPS 2023 RealML Workshop (Best Student Paper Award)
Accelerated scientific discovery through large multimodal models, Bayesian optimization, and autonomous robots.
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.
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.
Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations

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

NeurIPS 2020
Efficient multi-objective optimizer for expensive black-box functions.
Fluid Directed Rigid Body Control using Deep Reinforcement Learning

Fluid Directed Rigid Body Control using Deep Reinforcement Learning 🤖 🎨

ACM TOG / SIGGRAPH 2018
Deep RL can control high-dimensional fluid-rigid coupling dynamics.

Project

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

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

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

Autonomous Robotic Assembly of a Skateboard Truck 🤖

Autodesk Research Demo
Autonomous assembly of a mechanical skateboard truck with a flexible robotic system.

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)