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About

Michael Popp’s research lies at the intersection of human-robot interaction (HRI), emotion recognition, and physiological computing. His most influential work, “Emotions in robot psychology” (2014), has garnered 25 citations and explores how affective states can be modeled and interpreted in robotic systems. Popp made a foundational contribution with his “Real-time framework for multimodal human-robot interaction” (2009, 12 citations), which introduced an integrated architecture for processing speech, gestures, and other signals in real time—a key enabler for natural human-robot dialogue. He also advanced surgical robotics through his study on haptic feedback in robotic heart surgery (2005, 8 citations). A distinctive thread in Popp’s work is his focus on physiological signals: his 2008 paper on recognizing over- and underchallenge (4 citations) demonstrated that involuntary data like heart rate or skin conductance can reveal emotional states even when facial or vocal cues are absent. His 2009 study on emotion induction during HRI (3 citations) further validated this approach by evoking realistic, task-relevant emotions rather than artificial ones. Together, Popp’s research bridges engineering and psychology, offering practical frameworks for robots that sense and respond to human affect.