Ming–Chieh Lin

University of North Carolina at Chapel Hill

Papers

Total Citations

1,821

H-Index

About

Ming-Chieh Lin is a leading researcher in computer graphics and robotics, best known for pioneering work in multi-agent navigation and physics-based simulation. His seminal paper "Reciprocal n-Body Collision Avoidance" (2011) has garnered over 1,800 citations, introducing a decentralized, reciprocal velocity obstacle approach that enables hundreds of agents to navigate crowded environments without explicit coordination—a foundational technique now widely adopted in robotics, crowd simulation, and autonomous systems. More recently, Lin has advanced differentiable simulation with "Differentiable Simulation of Soft Multi-body Systems" (2022), which presents a novel method for integrating soft-body dynamics into gradient-based optimization pipelines. This work introduces a top-down matrix assembly algorithm within Projective Dynamics and a generalized dry friction model, enabling efficient gradient computation for soft articulated bodies. By bridging differentiable physics with machine learning, Lin's contributions are shaping the next generation of robotic control, character animation, and deformable object manipulation. His research continues to influence both academic and industrial applications, from autonomous navigation to soft robotics.