Papers
2
Total Citations
9
H-Index
2
About
Thomas Liang is a robotics researcher whose work bridges the critical gap between intuitive human-robot interaction and autonomous perception in extreme environments. His primary research areas include human-robot communication, affective computing, and planetary rover autonomy. Liang’s most impactful contribution, “An Approach to Elicit Human-Understandable Robot Expressions to Support Human-Robot Interaction” (2025, 7 citations), introduces a novel two-phase process for enabling robots to generate legible, human-interpretable expressions—a foundational step toward building trust and transparency in collaborative systems. He also led the development of POLAR-Sim, a simulation framework that augments NASA’s POLAR dataset (2,600+ high dynamic range stereo pairs across 13 lunar-analog terrain scenarios) to advance data-driven lunar perception and rover simulation. This work directly supports NASA’s Artemis mission goals by improving how robots navigate rocky, cratered landscapes under challenging lighting. With his dual focus on social robotics and extreme-terrain autonomy, Liang is shaping the future of robots that can both work alongside humans and explore the Moon.
Research Focus
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Top Papers
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