Ximi Hoque

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About

Ximi Hoque is a researcher at the forefront of human-computer interaction, specializing in affective computing and social signal processing. Their work focuses on enabling machines to understand and generate natural, context-aware nonverbal behaviors—particularly facial expressions—during dyadic conversations. Hoque’s most notable contribution is the BEAMER framework (Behavioral Encoder to Generate Multiple Appropriate Facial Reactions), introduced in a 2023 paper that has already garnered 11 citations. This system models the nuanced interplay between speaker and listener, allowing avatars and social robots to produce contextually suitable facial gestures in real time. By bridging the gap between raw conversational cues and expressive, human-like reactions, Hoque’s research directly enhances user experience in virtual agents, telepresence, and assistive robotics. Their work stands out for its emphasis on appropriateness and variability—moving beyond static or generic responses to generate a diverse range of believable listener behaviors. As the field increasingly demands more authentic human-machine interaction, Hoque’s contributions are laying critical groundwork for emotionally intelligent systems that can engage users with subtlety and social grace.