Education Data Science Conference
The Education Data Science Conference 2026 is a two-day forum for researchers, practitioners, and students to shape the future of education through data. We invite submissions that advance rigorous, ethical, and interdisciplinary approaches through using data in a variety of learning contexts. From classrooms to platforms, from theory to practice: Please join us to share new applications of methods, address challenges of teaching, learning, and policy, and push the boundaries of an evolving discipline in pursuit of better, more equitable educational outcomes.
Organizing Committee
(alphabetical order)
Dora Demszky
Assistant Professor of Education
ddemszky@stanford.edu
Dora is an Assistant Professor in Education Data Science at Stanford University. Her research combines natural language processing and input to from practitioners to develop and test tools for supporting teachers.
Katharine Sadowski
Assistant Professor of Education
ksadow@stanford.edu
Sadowski’s research bridges economics and public policy to examine how education and labor market policies shape the experiences of students, families, educators, and educational institutions. She combines econometric analysis with advanced machine learning methods to clean, link, and analyze large-scale administrative data for policy evaluation.
Sanne Smith
Lecturer
sannesmith@stanford.edu
Sanne Smith is a lecturer at the Stanford Graduate School of Education and is the Program Director of the Education Data Science MS Program. She teaches courses that introduce students to coding, data wrangling and visualization, various statistical methods, and the interpretation of quantitative research.
