Lisa Chen

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About

Lisa Chen’s research lies at the vital intersection of social robotics, human-robot interaction, and healthcare automation. Her most influential work, “A thermal emotion classifier for improved human-robot interaction” (2016, 29 citations), introduces a novel method for robots to detect human emotional states using thermal imaging. This contribution is foundational for developing robots that can adapt to users’ temperaments in long-term roles as tutors, home assistants, or healthcare aides—a critical step toward truly empathetic machines. Chen’s earlier work, “The application of robots and eye tracking devices in a general dentist’s clinic” (2013), explores practical automation in clinical settings, addressing instrument sterilization and workflow efficiency to reduce contamination and workplace hazards. Though less cited, this study demonstrates her commitment to translating robotic technologies into real-world, high-stakes environments. Together, her research bridges affective computing and applied robotics, offering tangible pathways for robots to serve alongside humans with both emotional intelligence and operational reliability. Chen’s contributions are shaping how we design robots that are not only functional but also socially aware.