Yi‐King Choi

Papers

Total Citations

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About

Yi-King Choi is a researcher whose work bridges computer graphics, robotics, and human-computer interaction, with a particular focus on understanding and modeling human-object interactions. Her most cited paper, "Learn to Predict How Humans Manipulate Large-Sized Objects From Interactive Motions" (2022, 21 citations), addresses a fundamental challenge in human-robot interaction and virtual reality: anticipating how people will manipulate large everyday objects based on their full-body motions. This work has implications for creating more intuitive and responsive robotic assistants and immersive virtual environments. Earlier, Choi contributed foundational geometric algorithms with her paper "Determining the directional contact range of two convex polyhedra" (2009, 5 citations), which provides mathematical tools for analyzing physical interactions between objects. Her research uniquely combines geometric computation with machine learning, enabling systems to not only understand current human actions but also predict future object states. This predictive capability is crucial for applications ranging from assistive robotics to surveillance, where anticipating human intent can improve safety and efficiency. Choi's work exemplifies how computational geometry and AI can work together to decode the complex dynamics of human manipulation.