Papers
28
Total Citations
956
H-Index
14
About
Louis-Philippe Morency is a leading figure in multimodal machine learning, a field he has helped define through pioneering work on how computers perceive and integrate human communicative signals—from language and tone to facial expressions and gestures. His foundational contributions are captured in the widely cited *Foundations & Trends in Multimodal Machine Learning* (2024, 150+ citations), which serves as a definitive roadmap for the discipline. Morency’s research has a strong human-centered focus, advancing automatic emotion recognition across the lifespan. He created the EmoReact dataset (2016, 117 citations) to enable emotion recognition in children, and later ElderReact (2019, 37 citations) to extend this capability to aging adults—critical steps for developing socially intelligent robots and affect-aware tutors. His earlier work on head pose estimation and gesture recognition (e.g., head-nod recognition in human-robot conversation, 2006, 104 citations) laid the technical groundwork for natural, non-verbal human-robot interaction. With over 800 citations across his top papers, Morency’s research bridges computer vision, affective computing, and conversational AI, shaping how machines understand us through the rich, multimodal tapestry of human communication.
Research Focus
Key Achievements
Top Papers
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- 3The effect of head-nod recognition in human-robot conversation104 citations · 2006
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- 6Recognizing gaze aversion gestures in embodied conversational discourse81 citations · 2006
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