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About

Michael Neff is a computer animation and human-computer interaction researcher whose work sits at the intersection of expressive movement, embodied agents, and nonverbal communication. His most influential contribution is a comprehensive review of data-driven co-speech gesture generation (2023, accumulating over 100 citations across versions), which has become a foundational reference for researchers developing believable virtual characters in film, games, and virtual social spaces. His early work on modeling tension and relaxation for physically based animation (2002, 67 citations) demonstrated how subtle muscular dynamics can convey emotion and intent — a problem that had long resisted computational treatment despite its centrality to traditional animation practice. Neff has also made notable contributions to the study of Laban Movement Analysis, investigating how Effort elements perceptually communicate intention, and has explored how gestural mimicry influences human preference for virtual agents. His Mimebot project examined how nonverbal expression transfers across radically different agent embodiments — from robots to game characters — addressing a critical challenge as artificial agents proliferate across diverse platforms. Across his career, Neff's research has advanced our understanding of how movement communicates meaning and how that knowledge can be computationally harnessed to create more natural, expressive animated characters.