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. Prof. Jordan was elected a member of the National Academy of Sciences (NAS) in 2010, of the National Academy of Engineering (NAE) 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 (AAAS). He has been named a Neyman Lecturer and a Medallion Lecturer by Institute of Mathematical Statistics (IMS). He is a Fellow of the IMS, a Fellow of the IEEE, a Fellow of the AAAI, and a Fellow of the ASA.
- X. Pan, D. Papailiopoulos, S. Omyak, B. Recht, K. Ramchandran, and M. Jordan, "Parallel correlation clustering on big graphs," Advances in Neural Information Processing Systems 28, Dec. 2015.
- X. Pan, S. Jegelka, J. E. Gonzalez, J. K. Bradley, and M. Jordan, "Parallel Double Greedy Submodular Maximization," in Advances in Neural Information Processing Systems 27, 2014.
- X. Pan, J. E. Gonzalez, S. Jegelka, T. Broderick, and M. Jordan, "Optimistic concurrency control for distributed unsupervised learning," in Advances in Neural Information Processing Systems 26, 2013, pp. 1403--1411.
- B. Taskar, S. Lacoste Julien, and M. Jordan, "Structured prediction, dual extragradient and Bregman projections," J. Machine Learning Research, vol. 7, pp. 1627-1653, Dec. 2006.
- F. R. Bach and M. Jordan, "Learning spectral clustering, with application to speech separation," J. Machine Learning Research, vol. 7, pp. 1963-2001, Dec. 2006.
- Y. W. Teh, M. Jordan, M. J. Beal, and D. M. Blei, "Hierarchical Dirichlet processes," J. American Statistical Association, vol. 101, no. 476, pp. 1566-1581, Dec. 2006.
- M. Jordan, "Graphical models," Statistical Science: Special Issue on Bayesian Statistics, vol. 19, no. 1, pp. 140-155, Feb. 2004.
- D. M. Blei, A. Y. Ng, and M. Jordan, "Latent Dirichlet allocation," J. Machine Learning Research, vol. 3, pp. 993-1022, Jan. 2003.
- M. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, "An introduction to variational methods for graphical models," Machine Learning, vol. 37, no. 2, pp. 183-233, Nov. 1999.
- D. Wolpert, Z. Ghahramani, and M. Jordan, "An internal forward model for sensorimotor integration," Science, vol. 269, pp. 1880-1882, Sep. 1995.
- M. Jordan and R. A. Jacobs, "Hierarchical mixtures of experts and the EM algorithm," Neural Computation, vol. 6, no. 2, pp. 181-214, March 1994.