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D'Mello's research is in the fields of affective and attentional computing, multimodal interaction, speech and discourse processing, and intelligent learning environments. His team conducts basic research on affective and cognitive states (e.g., confusion, boredom, mind wandering) across a range of interaction contexts, develops real-time computational models of these states, and integrates the models in affect- and attention- aware intelligent technologies. Their research uses a range of techniques such as eye tracking, speech recognition, physiological sensing, computer vision, nonlinear time series analyses, discourse modeling, and machine learning. Interaction contexts include intelligent learning environments, educational games, collaborative problem solving, classroom discourse, text, scene, and film comprehension. Data is collected in the lab, online, and in schools.
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User Modeling, Adaptation, and Personalizationpp.120-131, (2024)
COGNITIVE SCIENCEno. 1 (2024): e13398-e13398
COGNITION & EMOTIONno. 1 (2024): 171-179
LAKpp.725-735, (2024)
LEARNING AND INSTRUCTION (2024): 101872
Rosy Southwell,Wayne Ward,Viet Anh Trinh,Charis Clevenger, Clay Clevenger, Emily Watts,Jason Reitman,Sidney D’Mello,Jacob Whitehill
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)pp.12291-12295, (2024)
Chelsea Chandler,Thomas Breideband,Jason G. Reitman, Marissa Chitwood,Jeffrey B. Bush, Amanda Howard, Sarah Leonhart,Peter W. Foltz,William R. Penuel,Sidney K. D'Mello
FOURTEENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, LAK 2024pp.576-586, (2024)
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