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Matthias W. Seeger received the Diplom degree (distinction) from Karlsruhe university, Germany, in 1999, his Ph.D. from Edinburgh university, UK, in 2003. He was a research fellow with Michael Jordan and Peter Bartlett, UC Berkeley, from 2003, and with Bernhard Schoelkopf, Max Planck Institute, Tuebingen, Germany, from 2005. He led a research group at Saarbruecken university, Germany, from 2008. He has joined EPFL in fall 2010.
Matthias Seeger made seminal contributions to theory and practice of Gaussian processes in machine learning, PAC-Bayesian learning theory, and large scale variational approximate Bayesian inference. He was invited fellow at the Newton institute program on high-dimensional statistics in 2008. He served in senior program committees of leading machine learning conferences (NIPS 2004, 2010; UAI 2009; AISTATS 2010; ICML 2011).
His research interests are in probabilistic Bayesian machine learning, large scale variational inference and nonparametric GP methods, with applications to image processing and imaging.