Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research in recent years has focused on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in signal processing, statistical genetics, computational biology, information retrieval and natural language processing.
Professor Jordan was elected a member of the National Academy of Sciences in 2010, of the National Academy of Engineering in 2010, and of the American Academy of Arts and Sciences in 2011. He is a Fellow of the American Association for the Advancement of Science. He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He is also a Fellow of the IMS, a Fellow of the IEEE, a Fellow of the AAAI, and a Fellow of the ASA.
- Learning and Games, Spring 2022. Workshop Organizer.
- Computational Complexity of Statistical Inference, Fall 2021. Visiting Scientist.
- Theory of Reinforcement Learning, Fall 2020. Visiting Scientist.
- Foundations of Deep Learning, Summer 2019. Visiting Scientist.
- Foundations of Machine Learning, Spring 2017. Visiting Scientist.
- Theoretical Foundations of Big Data Analysis, Fall 2013. Visiting Scientist, Program Organizer and Workshop Organizer.