Invited Speakers


Sally A. Goldman
Sally A. Goldman

Sally Goldman received her ScB from Brown University, and her M.S. and Ph.D. from MIT working under the guidance of Ron Rivest. She joined that faculty of Washington University in St. Louis in 1990 and served as the Associate Chair for 10 years. In June 2008, she joined Google as a research scientist, and is currently on leave from Washington University. Her research is in the area of algorithm design and analysis and machine learning with a recent focus on applications to image retrieval. She is an area chair for NIPS 2010, was the program committee co-chair for COLT 2000, and has served on the ICML and program committee numerous times. She is also on the editorial board of JMLR and JCSS. She has received many awards and honors including an NSF National Young Investigator Award, the Emerson Excellence in Teaching Award, and the Governor's Award for Excellence in Teaching. Sally and her husband, Ken Goldman, have recently published a book entitled, A Practical Guide to Data Structures and Algorithms using Java. Sally balances her career with raising her 3 children who are now 23, 19 and 13, and she enjoys participating in almost any sport or outdoor activity.


Raquel Urtasun
Raquel Urtasun

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, teaching a new class on Human Motion Analysis. 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, where she worked with Prof. Trevor Darrell. 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 previously worked as a research assistant at the Ecole National Superior de Telecomunication (ENST) in Paris. She graduated as an Electric Engineer in the Universidad Publica de Navarra, Pamplona, Spain and did her Master Thesis in Eurecom, France. She is an area chair of the NIPS 2010 conference, and served in the committee of numerous international computer vision and machine learning conferences (e.g., CVPR, ICCV, ICML). Her major interests are machine learning, computer vision and computer Graphics.


Ming Hua
Ming Hua

Ming Hua received her Ph.D. degree in Computing Science from Simon Fraser University, Canada, in 2009. Her Ph.D. dissertation focuses on ranking uncertain data. She joined Facebook as a Research Scientist in 2009. Her research is highly interdisciplinary and application-driven. She has the particular expertise in applying statistics in data mining and machine learning. Ming has published in premier journals including IEEE TKDE and the VLDB Journal, as well as premier academic conferences including ACM SIGKDD, VLDB, IEEE ICDE, and ACM SIGMOD. Ming is one of the Exhibits and Demos Co-Chairs for the 2011 IEEE International Conference on Data Mining (ICDM 2011). She was the publicity chair of the First ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (U.09), in conjunction with SIG KDD 2009. She served in the Program Committees of numerous International Conferences such as SIGKDD, ICDM and PAKDD.


Isabelle Guyon
Isabelle Guyon

Isabelle Guyon is an independent engineering consultant, specialized in statistical data analysis, pattern recognition and machine learning techniques. Her areas of expertise include handwriting recognition, biometrics, and bioinformatics. She has organized several machine learning competitions for which she received two NSF awards. Her recent interest is in applications of machine learning to the discovery of causal relationships. She is coordinating the "Causality Workbench", a project to benchmark causal discovery algorithms. Prior to starting her consulting practice in 1996, Isabelle Guyon was a researcher at AT&T Bell Laboratories, where she pioneered applications of neural networks to pen computer interfaces and invented Support Vector Machines (in collaboration with B. Boser and V. Vapnik). Isabelle Guyon holds a Ph.D. degree in Physical Sciences of the University Pierre and Marie Curie of Paris, France. She is vice-president of the Unipen foundation, action editor of the Journal of Machine Learning Research, demonstration chair of the NIPS 2010 conference, and competition chair of the IJCNN 2011 conference.