Raquel Urtasun is an Asssistant Professor at TTI-Chicago a
philanthropically endowed academic institute located in the campus of
the University of Chicago. She was a visiting professor at ETH Zurich
during the spring semester of 2010. Previously, she was a postdoctoral
research scientist at UC Berkeley and ICSI. Before that, she was a
postdoctoral associate at the Computer Science and Artificial
Intelligence Laboratory (CSAIL) at MIT. Raquel Urtasun completed her PhD at the Computer
Vision Laboratory, at EPFL, Switzerland in 2006 working with Pascal
Fua and David Fleet at the University of Toronto. She has been area
chair of NIPS 2010, 2011, 2012 and UAI 2012, as well as NIPS Workshop co-Chair in 2012. She has also served in the committee of numerous
international computer vision and machine learning conferences (e.g.,
CVPR, ICCV, ECCV, ICML, NIPS). Her major interests are statistical
learning and computer vision, with a particular interest in
non-parametric Bayesian statistics, latent variable models, structured
prediction and their application to scene understanding.
Neil Lawrence received his bachelor's degree in Mechanical Engineering from the University of Southampton in 1994. Following a period as an field engineer on oil rigs in the North Sea he returned to academia to complete his PhD in 2000 at the Computer Lab in Cambridge University. He spent a year at Microsoft Research in Cambridge before leaving to take up a Lectureship at the University of Sheffield, where he was subsequently appointed Senior Lecturer in 2005. In January 2007 he took up a post as a Senior Research Fellow at the School of Computer Science in the University of Manchester where he worked in the Machine Learning and Optimisation research group. In August 2010 he returned to Sheffield to take up a collaborative Chair in Neuroscience and Computer Science.
Neil's main research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application. He has a particular focus on applications in computational biology, but happily dabbles in other areas such as speech, vision and graphics. His main publication area from a methodological perspective is Gaussian processes. He is know for two particular formalisms based on Gaussian process models: Latent Force Models and Gaussian Process Latent Variable Models.
Neil is an Associate Editor in Chief for IEEE Transactions on Pattern Analysis and Machine Intelligence and an Action Editor for the Journal of Machine Learning Research. He was the founding editor of the JMLR Workshop and Conference Proceedings and is currently series editor. He is Program Chair for AISTATS 2012 and has served on the program committee of several international conferences and was an area chair for the NIPS conference in 2005 and 2006. He was general chair of AISTATS in 2010 (bringing the conference to Europe for the first time) and NIPS Workshop Chair, also in 2010.