The DSI Education Working Group discusses, identifies, and develops resources, curriculum examples, and innovative pedagogies as research on data science education for improving Columbia’s overall capacity in teaching data literacy, data ethics, empirical reasoning skills, advanced computational, and data-driven research skills.
The series is open to Columbia University faculty members and affiliated senior researchers who are interested in creative research on pedagogies and curriculum development. If you’d like to join these meetings, contact Erin Elliott, Events and Marketing Coordinator at ee2548@columbia.edu.
New programs for the 2026 – 2027 academic year will be announced soon!
Date of Talk: Monday, April 20, 2026
Host: Jeff Goldsmith, Associate Director for Education, Data Science Institute; and Associate Professor of Biostatistics, Mailman School of Public Health
Host: James David, Sr. Project Director, HEALing Communities Study, School of Social Work
Topic: Continuing the DSI Data Science Education working group’s ongoing faculty dialogue series on AI in education, this session will focus on the area of social work education. The lunch dialogue will bring together faculty to engage in a cross-disciplinary conversation centered on the ethical and practical integration of AI within the social work field. The session aims to create a dedicated space to explore how AI is reshaping community practice, curricular priorities, and teaching. By sharing insights, the dialogue aims to create professional connections across the university and build a shared understanding of the varied challenges of responsible AI pedagogy.
Date of Talk: Monday, March 9, 2026
Host: Tian Zheng, Professor of Statistics, Department of Statistics, Columbia University
Topic: Continuing the DSI Data Science Education working group’s faculty dialogue series on AI in education, the lunch dialogue event brings together faculty who lead or teach in data science programs with particular emphasis on faculty at CUIMC for an open, cross-disciplinary conversation on AI in education. The goal of the session is to create space for dialogue around how AI is affecting teaching, learning, and curricular priorities in medicine, public health, nursing, and dentistry; to deepen connections; and to begin building shared perspectives across disciplines.
Date of Talk: Monday, February 23, 2026
Topic: Kicking off DSI Data Science Education working group’s faculty dialogue series on AI education, the first lunch dialogue event brings together faculty who lead or teach in data science programs with invited humanities faculty for an open, cross-disciplinary conversation on AI education. The goal of the session is to create space for dialogue around how AI is affecting teaching, learning, and curricular priorities in the humanities, to deepen connections, and to begin building shared perspectives across disciplines.
Date of Talk: Monday, December 8, 2025
Speaker: Tian Zheng, Professor of Statistics, Department of Statistics, Columbia University
Speaker: Susan McGregor, Research Scholar, Data Science Institute, Columbia University
Abstract: Artificial Intelligence (AI) is transforming the way that both students and educators approach the teaching and learning process. In this free-flowing session, we’ll discuss various approaches to integrating (and limiting) AI into courses and assignments, and the considerations that are emerging for both students and faculty both at Columbia University and beyond.