David Blei

David Blei is a Professor of Computer Science and Statistics at Columbia University, holding dual appointments in Columbia Engineering and the Faculty of Arts and Sciences. He joined Columbia in 2014 after serving as an Associate Professor of Computer Science at Princeton University. His research focuses on probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference, with applications in text, images, social networks, and scientific data.

Education:

• Bachelor’s in Computer Science and Mathematics, Brown University (1997)
• PhD in Computer Science, University of California, Berkeley (2004)

Research Interests:

• Probabilistic modeling and Bayesian methods
• Machine learning applications in social and biological sciences
• Causal inference and fairness in AI
• Generative models and representation learning

Awards:

• Sloan Fellowship (2010)
• Office of Naval Research Young Investigator Award (2011)
• Presidential Early Career Award for Scientists and Engineers (2011)
• Blavatnik Faculty Award (2013)

Advising & Grants: Professor Blei has advised numerous students and led interdisciplinary research projects, though specific grant details are not explicitly listed. His work bridges theoretical foundations with practical applications in healthcare, economics, and social science.

Labs & Affiliations: Affiliated with Columbia’s Foundations of Data Science, Computing Systems for Data-Driven Science, and Computational Social Science centers, advancing interdisciplinary data science initiatives.