Michael I. Jordan
Also known as Michael Jordan Michael I Jordan
Michael I. Jordan helped build the statistical foundations of machine learning. He studied psychology, mathematics and cognitive science, then worked at MIT before joining Berkeley in 1998. With Zoubin Ghahramani, Tommi Jaakkola and Lawrence Saul, he explained variational methods that make difficult probability calculations more tractable. With David Blei and Andrew Ng, he introduced Latent Dirichlet Allocation, a model that describes documents through mixtures of topics. His broader work links learning with optimization and decisions among interacting participants. Jordan became a Berkeley professor emeritus in 2024. He currently holds a research appointment at Inria and École Normale Supérieure, where the Markets and Learning chair connects statistical learning with market design.
- Works
- 1,024
- Citations
- 187,799
- h-index
- 159
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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1978–1985
Studying psychology, mathematics and cognition
Completed degrees in psychology, mathematics and cognitive science.
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1998
Joining Berkeley across two fields
Joined Berkeley with appointments in computer science and statistics.
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1999
Explaining approximate probabilistic inference
Coauthored an introduction to variational methods for graphical models.
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2003
Modeling topics in document collections
Introduced Latent Dirichlet Allocation with David Blei and Andrew Ng.
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2024
Taking a research role in France
Took an Inria and École Normale Supérieure research role and led the Markets and Learning chair.
Sources and credits
Photo: University of California, Berkeley faculty profile. License: Not stated by source. Source: www2.eecs.berkeley.edu. Cropped to a square and resized. Ask us to remove or replace this photo.