Azevedo is a professor in the School of Modeling Simulation and Training. He is also an affiliated faculty in the Department of Computer Science and the Department of Internal Medicine at the University of Central Florida and is the lead scientist for the Learning Sciences Faculty Cluster Initiative. He received his PhD in educational psychology from McGill University and completed his postdoctoral training in Cognitive Psychology at Carnegie Mellon University. His main research area includes examining the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, multimedia, simulations, serious games, immersive virtual learning environments). More specifically, his overarching research goal is to understand the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, emotional, motivational, and social processes and their impact on learning, performance, and transfer. To accomplish this goal, he conducts laboratory, classroom, and in-situ (e.g., medical simulator) studies and collects multi-channel data to develop models of human-computer interaction; examines the nature of temporally unfolding self- and other-regulatory processes (e.g., human-human and human-artificial agents); and designs intelligent learning and training systems to detect, track, model, and foster learners, teachers, and trainers’ self-regulatory processes.