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Sidney D’Mello is an Associate Professor at the Institute of Cognitive Science and the Department of Computer Science at the University of Colorado Boulder (since July 1, 2017). He was previously an Associate Professor in the departments of Psychology and Computer Science at the University of Notre Dame.

D'Mello leads the NSF National Institute for Student-Agent Teaming (2020-2025), which aims to develop AI technologies to facilitate rich socio-collaborative learning experiences for all students.

D'Mello's research is at the intersection of the cognitive, affective, computing, and learning sciences. Specific interests include affective computing, social signal processing, intelligent learning environments, speech and language processing, human-computer interaction, and multimodal machine learning. His team is interested in the dynamic interplay between cognition and emotion while individuals and groups engage in complex real-world tasks. We apply insights gleaned from this basic research program to develop intelligent technologies that help people achieve to their fullest potential by coordinating what they think and feel with what they know and do.

Announcements

  • Learn about our U.S. National Science Foundation (NSF) AI Institute for Student-AI Teaming. here

  • Prospective PhD students - see here for details.

  • New paper: Mind wandering during reading: A review of cognitive Mind wandering during reading: A review of cognitive, behavioral, computational, and intervention research in Language and Linguistics Compass. [PDF]

  • New paper: Jointly predicting job performance, personality, cognitive ability, affect, and well-being. IEEE Computational Intelligence Magazine. [PDF]

  • New paper: Examining Response to Negative Life Events through Fitness Tracker Data. [PDF]

  • New paper: Breaking out of the Lab: Mitigating Mind Wandering with Gaze-Based Attention-Aware Technology in Classrooms in CHI 21.[PDF]

  • New paper:  A Deep Transfer Learning Approach to Automated Teacher Discourse Feedback in LAK 21. [PDF]

  • New paper:  What You Do Predicts How You Do: Prospectively Modeling Student Quiz Performance Using Activity Features in an Online Learning Environment in LAK 21.[PDF]

This 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. The interaction contexts include educational games, collaborative problem solving, classroom discourse, computerized reading, and workplace activities. Data is collected in the lab, online, in schools, and the workplace.

D'Mello has co-edited seven books and has published more than 300 journal papers, book chapters, and conference proceedings in these areas. He is an associate editor for Discourse Processes and formerly for IEEE Transactions on Affective Computing, IEEE Transactions on Learning Technologies, International Journal of Artificial Intelligence in Education, PLoS ONE, and IEEE Access. He serves on the editorial boards of User Modeling & User-Adapted Interaction and Affective Science. D'Mello also serve(d) on the executive board of the International Artificial Intelligence in Education Society, the International Educational Data Mining Society, and the Association for the Advancement of Affective Computing.

Download CV here