Zachary Pardos

Associate Professor of Education and Information at UC Berkeley

Dr. Pardos is an Assistant Professor at UC Berkeley in the Graduate School of Education with a joint appointment in the iSchool. His research focuses on knowledge representation and personalized supports leveraging big data in education. His current projects are centered around increasing upward mobility in public post-secondary systems and using behavioral and semantic data to map out paths to cognitive and career achievement. He has published over 50 peer-reviewed papers relating to learning analytics and given talks on big data, ethics, and education before the National Academy of Education and the White House Office of Science and Technology Policy. 

He holds several academic leadership positions in AI and Education, including serving on the executive committee of the Artificial Intelligence in Education Society, the editorial boards of the Education Data Mining and AI in Education journals, and serving as program committee member for the 2019 conferences: ACM Learning Analytics and Knowledge, ACM Learning @ Scale, ACM Recommender Systems, Educational Data Mining, and AI in Education. He earned his PhD in Computer Science at Worcester Polytechnic Institute. Funded by a National Science Foundation fellowship, he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. In 2013, he completed his post-doc studying massive open online courses at the Massachusetts Institute of Technology. At UC Berkeley, he directs a research lab on Computational Approaches to Human Learning (CAHL) and teaches courses on data mining and analytics, digital learning environments, and machine learning in education. Recently, he received an AI educator award from the AAAI conference meant to support teachers with ideas for making AI relevant to the social sciences.