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About

Mai Lee Chang is a researcher at the forefront of human-robot interaction (HRI), with particular expertise in collaborative robotics, fairness in human-robot teams, and automation integration. Her work bridges cognitive science and robotics engineering to address how humans and robots can work together more effectively and equitably. Chang's most influential contribution—her 2018 paper on integrated intent recognition and communication, with 25 citations—demonstrated that combining a robot's ability to predict human motion with intentional robot movement significantly improves collaborative physical tasks. Complementing this, her research on contingency detection (13 citations) introduced novel algorithms enabling robots to recognize human reactions in unpredictable real-world environments. Perhaps most distinctively, Chang has pioneered the study of fairness in human-robot teaming. Through a series of papers spanning 2020–2022, she examined how humans perceive equitable treatment from robotic teammates, finding that fairness extends beyond task distribution to include transparency and effort recognition—a nuanced insight with growing relevance as workplace robots become widespread. Her early work with NASA on human-automation integration for deep-space exploration missions further underscores her range. With nearly 75 total citations across diverse topics, Chang's research is shaping how future robotic systems are designed to be not just capable, but genuinely collaborative and fair.