Sidney D'MelloDr. Sidney D’Mello

Sidney D’Mello is an Assistant Professor in the departments of Computer Science and Psychology at the University of Notre Dame.  His primary research interests are in the affective, cognitive, learning, and computing sciences.  More specific interests include affective computing, artificial intelligence, human-computer interaction, natural language understanding, and computational models of human cognition.  He has co-edited five books and has published over 200 journal papers, book chapters, and conference proceedings in these areas.  D’Mello’s work has received 11 best/outstanding paper awards at international conferences, has been featured in several media outlets including the Wall Street Journal, and has been supported by the National Science Foundation, Institute for Education Sciences, and the Gates, Raikes, Templeton, and Walton Foundations.  D’Mello is an associate editor for IEEE Transactions on Affective Computing, IEEE Transactions on Learning Technologies, and IEEE Access and serves on the editorial boards of Frontiers in Psychology — Human Media Interaction, International Journal of Artificial Intelligence in Education, Discourse Processes, and User-Modeling and User-Adapted Interaction.  He also serves on the executive boards of the International Artificial Intelligence in Education Society and Educational Data Mining Society.  D’Mello received his PhD. in Computer Science from the University of Memphis in 2009.

On October 22, from 12:30 until 1:30pm, in LINK Lab (246 Nedderman Hall)
Dr. D’Mello delivered the following public presentation:

Title: Affect- and Attention- Aware Cyberlearning

We believe that next-generation learning technologies should have some mechanism to sense and respond to students’ affective and attentional states in addition to their knowledge levels.  Towards this end, we have been engaging in computational modeling of affective and attentional states (e.g., confusion, frustration, engagement, and mind wandering) using facial features, linguistic and paralinguistic aspects of speech, body movements, peripheral physiology, eye gaze, and interaction and contextual cues, in a variety of digital learning environments ranging from educational games and intelligent tutoring systems to simple interfaces that support reading comprehension and problem solving.  These computer models are embedded in advanced learning technologies that dynamically tailor their instructional strategies in a manner that is sensitive to students’ affective and attentional states.  This talk will discuss the theoretical foundation of our work and will summarize recent results and key insights towards building affect- and attention- aware instructional strategies.