Juncheng Li
Robotics · Embodied AI · Sim-to-Real

Juncheng (Jason) Li

李俊成
Associate Professor, Soochow University
School of Mechanical & Electrical Engineering · Ex-Amazon Applied Scientist II

I build perception and manipulation systems that let robots grasp and act reliably in cluttered, real-world environments — bridging large-scale simulation, embodied AI, and computer vision.

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Juncheng (Jason) Li
Recruiting · Fall 2026

Looking for master's students

I am recruiting motivated master’s students for Fall 2026 in robotic manipulation, embodied AI, and simulation. Interested? Email me at ljc312463566@gmail.com.

Email to apply
About

Bringing reliable autonomy to physical robots

Juncheng Li with Prof. David Cappelleri and a mobile manipulator at Purdue MSRAL
With Prof. David Cappelleri and our mobile manipulator at Purdue’s MSRAL.
Education

Education

2020 – 2024

Ph.D., Mechanical Engineering

Purdue University, West Lafayette, IN
Advisor: David J. Cappelleri
2018 – 2019

M.S.E., Robotics

University of Pennsylvania (GRASP Lab)
Advisor: Mark Yim
2015 – 2018

B.E., Mechanical Engineering

Stony Brook University, Stony Brook, NY
Advisor: Benjamin Lawler
Experience

Experience

2025 – Present

Associate Professor

School of Mechanical & Electrical Engineering, Soochow University
2024 – 2025

Applied Scientist II

Amazon Robotics, North Reading, MA
Amazon Science profile ↗
2023

Applied Scientist Intern

Amazon Robotics, North Reading, MA
2020 – 2024

Graduate Research Assistant

MSRAL, Purdue University · NASA RETHi
RETHi 2025 Impact Report ↗
Latest

News

In the Media

Publications

Selected Research

Peer-reviewed work on grasping, manipulation, and pose estimation. Full list on Google Scholar.

Sim-Grasp

Sim-Grasp: Learning 6-DOF Grasp Policies for Cluttered Environments Using a Synthetic Benchmark

Juncheng Li, David J. Cappelleri
IEEE Robotics and Automation LettersRA-L
Project Paper Code
Sim-Suction

Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic Benchmark

Juncheng Li, David J. Cappelleri
IEEE Transactions on RoboticsT-RO
Project Paper Code
Sim-MEES

Sim-MEES: Modular End-Effector System Grasping Dataset for Mobile Manipulators in Cluttered Environments

Juncheng Li, David J. Cappelleri
arXiv preprint, 2023
Paper Code
Modular End-Effector

Modular End-Effector System for Autonomous Robotic Maintenance & Repair

Juncheng Li, Clark Teeple, Robert J. Wood, David J. Cappelleri
IEEE International Conference on Robotics and AutomationICRA
Paper Video
Pose Estimation

Neural Network-Based Pose Estimation Approaches for Mobile Manipulation

Arindam B. Chowdhury, Juncheng Li, David J. Cappelleri
ASME Journal of Mechanisms and RoboticsJMR
Paper Video
Pose Estimation Comparison

Comparison of Neural Network-Based Pose Estimation Approaches for Mobile Manipulation

Arindam B. Chowdhury, Juncheng Li, David J. Cappelleri
ASME IDETC-CIE, 2021
Paper
Honors

Honors & Honor Societies

Teaching & Service

Academic Contributions

Teaching

  • Graduate Teaching Assistant & Lab Coordinator — ME 263: Introduction to Mechanical Engineering Design, Innovation & Entrepreneurship, Purdue University (Fall 2022)

Conference Peer Review

  • IEEE International Conference on Robotics and Automation (ICRA)
  • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • IEEE-RAS International Conference on Soft Robotics (RoboSoft 2023)

Journal Peer Review

  • IEEE Transactions on Robotics (T-RO)
  • IEEE Robotics and Automation Letters (RA-L)
  • IEEE Robotics and Automation Practice (RA-P)
  • IEEE Transactions on Automation Science and Engineering (T-ASE)
  • IEEE Transactions on Human-Machine Systems (T-HMS)
  • Artificial Intelligence (Elsevier)
  • Scientific Reports (Springer Nature)
Prospective Students · Fall 2026

Join my group

I am recruiting master's students in robotic manipulation, embodied AI, and simulation for Fall 2026. If that sounds like you, get in touch with your CV and transcript.