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Zachary Pardos is an Associate Professor in the Berkeley School of Education at the University of California, Berkeley, where he studies adaptive learning and artificial intelligence. His research primarily focuses on knowledge representation and recommender systems designed to enhance upward mobility in postsecondary education, employing behavioral and semantic data analytics. Pardos earned his PhD in Computer Science from Worcester Polytechnic Institute. His dissertation addressed computational models of cognitive mastery, leading him to work extensively with K-12 educators and students on integrating educational technology into curricula. He completed a Postdoctoral fellowship at the Massachusetts Institute of Technology. At UC Berkeley, he directs the Computational Approaches to Human Learning research lab, teaches data science courses, and is an affiliated faculty member in Cognitive Science.
Massachusetts Institute of Technology • Cambridge, MA, USA
Conducted research in learning sciences, focusing on the integration of AI in educational contexts.
University of California, Berkeley • Berkeley, CA, USA
Directs the Computational Approaches to Human Learning research lab and teaches courses in data science.
The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.