Yi-Chi Liao

Aalto University, National Taiwan University, ETH Zurich

Papers

Total Citations

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About

Yi-Chi Liao is a leading researcher at the intersection of human-computer interaction, robotics, and cognitive science, with a focus on how humans perceive and physically interact with technology. Her most influential work, "Rediscovering Affordance: A Reinforcement Learning Perspective" (2022, 21 citations), proposes a groundbreaking theoretical framework that explains how affordances—the perceived action possibilities of objects—are discovered and adapted through interaction, filling a critical gap in HCI theory. Liao is also a pioneer in supernumerary robotic limbs (SRLs), contributing the "3HANDS Dataset" (2025) to enable naturalistic handover motions between robotic appendages and humans, a key step toward seamless human augmentation. Her earlier work on "ThirdHand" (2015) explored haptic feedback for mobile gaming, demonstrating her sustained interest in enhancing embodied interaction. By bridging reinforcement learning, robotics, and perceptual psychology, Liao’s research provides both theoretical foundations and practical datasets that advance our understanding of how humans learn to use tools and how machines can assist them. Her work is essential reading for anyone studying affordance theory, wearable robotics, or human-robot collaboration.