CV

B.Eng.

Tongji University

Mechanical Engineering

GPA: 4.28/5.0 (87.78/100)

• School of Mechanical Engineering
• Core Courses: Robotics, Machine Vision, Automatic Control Theory, Mechanical Design, Microcontroller Systems
• CET-6: 510

Hardware-Software Co-Design of a Dual-Vision, Infinite-Roll Hand for Edge-Native Grasping

IEEE/ASME ICARM 2026, Paris, France (Accepted)

First-author and corresponding-author paper from Tongji University on edge-native language-guided grasping with a dual-vision infinite-roll dexterous hand.

Folding Cane Chair — Utility Model Patent Application

China National Intellectual Property Administration

Utility model patent application accepted by CNIPA. Application No. 202521174680.9; filing date: June 9, 2025; applicant and inventor: Mingyu Li.

Project Lead — Panoptic-Grasp: Dual-Vision, Infinite-Roll Dexterous Hand for Edge-Native Zero-Shot Grasping

Tongji University, Vision4Robotics (V4R) Lab

• Supervised by Assoc. Prof. Changhong Fu
• Mechanical: Designed a 6-DOF dexterous hand with a direct-drive slip-ring wrist enabling infinite continuous roll; full mechanical design in Autodesk Inventor with custom 12 V power distribution
• Perception: Built a dorsal–ventral dual-camera relay for complementary front/rear perception; deployed reparameterized YOLO-World on RK3588 NPU for real-time language-guided zero-shot grasping (offline text-encoder reparameterization removes online inference overhead)
• System: Integrated full perception-to-actuation loop on ROS 2 (Python & C++); validated on a physical platform, closing the Sim-to-Real gap
• Outcome: First-author & corresponding-author paper accepted by IEEE/ASME ICARM 2026

Team Member — Precise Grasping of Manipulator Under 2D-Camera and Embedded-System Constraints

Tongji University

• Optimized the manipulator grasping pipeline under 2D planar camera and low-computing-power embedded system constraints
• Conducted mechanical design of the manipulator and deployed visual / grasping algorithms on the embedded platform
• Project served as a precursor to the Panoptic-Grasp edge-deployment work in the V4R Lab

Team Member — Manual Work Simulation & Optimization in an Intelligent Manufacturing System (ema Work Designer)

Tongji University

• Built a digital-twin gearbox assembly line in ema Work Designer
• Conducted quantitative ergonomic analysis and proposed workstation reconfigurations to improve workers’ working environment
• Completed gearbox modeling and contributed to the digital-twin workflow toolchain

First-Class Scholarship & Outstanding Student Award

Tongji University

Awarded for top academic performance and overall excellence.

Higher Education Cup — National First Prize (Additive Manufacturing)

Ministry of Education / China Graphics Society

18th National College Student Advanced Graphics Technology and Product Information Modeling Innovation Competition.

Shanghai Mechanical Engineering Innovation — Municipal First Prize

Shanghai Municipal Education Commission

14th Shanghai College Student Mechanical Engineering Innovation Competition.

Shanghai Mechanical Design Innovation — Municipal First Prize & National Final Recommendation

Shanghai Municipal Education Commission / 12th National Mechanical Design Innovation Competition

15th Shanghai Mech Innovation Competition; project Smart Shrimp Peeling — vision-guided integrated shrimp pre-processing platform; core member for control, vision, and partial mechanical design.

Higher Education Cup — National Second Prize (Team)

Ministry of Education / China Graphics Society

18th Higher Education Cup — Team event.

BMHRI Cup Mechanical Innovation — National Third Prize

Chinese Mechanical Engineering Society

China College Student Mechanical Engineering Innovation and Creativity Competition.

National Intelligent Car Race — Regional Second Prize

Chinese Association of Automation

20th National University Students Intelligent Car Race — Baidu Smart Transportation Track.

China International College Students' Innovation Competition — University Silver Award

Ministry of Education

Industry Track, university-level selection.