Hung Yu Ling

Papers

Total Citations

104

H-Index

About

Hung Yu Ling is a leading researcher in computer animation and physics-based character control, with a primary focus on locomotion and motor skill learning. His most influential work, "ALLSTEPS: Curriculum‐driven Learning of Stepping Stone Skills," has garnered nearly 100 citations, establishing him as a key figure in solving the longstanding challenge of stepping-stone locomotion—a problem where characters must navigate environments with fully constrained foot placements. Ling’s major contribution lies in developing a curriculum-driven reinforcement learning framework that enables virtual characters to master complex, precise foot placement strategies, mimicking human adaptability in constrained terrains. This work bridges the gap between animation and robotics, offering scalable solutions for realistic movement synthesis. Beyond ALLSTEPS, Ling’s research advances the broader field of physics-based simulation, where his methods demonstrate how structured training curricula can dramatically improve skill acquisition in embodied agents. His achievements highlight a deep understanding of biomechanics and machine learning, making his work essential reading for students and researchers interested in character animation, robotic locomotion, and the intersection of artificial intelligence with physical simulation.