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Introduction of New Associate Editors


Pages: pp. 961-963

We are happy to announce the appointment to the TPAMI Editorial Board of Francis Bach, Horst Bischof, Pedro F. Felzenszwalb, Arthur Gretton, Aleš Leonardis, Ravi Ramamoorthi, Charles V. Stewart, and John Winn. At the same time, we would also like to express our gratitude to Thomas Hofmann, Daniel Lopresti, B.S. Manjunath, Marc Pollefeys, Bernhard Schoelkopf, Jianbo Shi, and Harry Wechsler, who have retired as Associate Editors. Their contributions to the journal over the years is greatly appreciated.

Dr. Bach will oversee papers in machine learning and clustering. Professor Bischof will handle submissions in object recognition, visual learning, tracking, and surveillance. Professor Felzenszwalb will be in charge of papers in learning, object recognition and optimization. Dr. Gretton will be responsible for papers on kernel methods, Gaussian process methods, statistical learning theory, blind source separation, and hypothesis testing. Professor Leonardis will oversee papers in object recognition and categorization, scene recognition, and statistical visual learning. Professor Ramamoorthi will be handling papers in the areas of lighting, reflectance, image-based rendering, and appearance acquisition. Professor Stewart will be in charge of papers in statistical computer vision and medical imaging. Dr. Winn will cover papers in object recognition and statistical machine vision.

Brief biographies appear below. Welcome aboard, and thank you in advance for all your hard work!

Ramin Zabih, Editor-in-Chief

Zoubin Ghahramani, Associate Editor-in-Chief

Jiri Matas, Associate Editor-in-Chief

About the Authors

Francis Bach graduated from the École Polytechnique, Palaiseau, France, in 1997, and received the PhD degree in 2005 from the Computer Science Division at the University of California, Berkeley. He is a researcher in the Willow INRIA project-team, in the Computer Science Department of the École Normale Supérieure, Paris, France. His research interests include machine learning, statistics, optimization, graphical models, kernel methods, and statistical signal processing.
Horst Bischof received the MS and PhD degrees in computer science from the Vienna University of Technology in 1990 and 1993, respectively. In 1998, he received the Habilitation (venia docendi) for applied computer science. Currently, he is a professor at the Institute for Computer Graphics and Vision at the Technical University Graz, Austria. He is a member of the scientific boards of the applied research centers ECV, VrVis, and KNOW. He is a board member of the Fraunhofer Institut für Graphische Datenverarbeitung (IGD). His research interests include object recognition, visual learning, motion and tracking, visual surveillance and biometrics, medical computer vision, and adaptive methods for computer vision, where he has published more than 380 peer reviewed scientific papers. Professor Bischof was cochairman of international conferences (ICANN, DAGM) and local organizer for ICPR ’96. He was program cochair of ECCV ’06 and area chair of CVPR ’07, ECCV ’08, CVPR ’09, and ACCV ’09. Currently, he is an associate editor for Pattern Recognition, Computer and Informatics, and the Journal of Universal Computer Science. He has received several awards, among them the 29th Pattern Recognition award in 2002, the main prize of the German Association for Pattern Recognition DAGM in 2007, the Best Scientific Paper award at BMCV ’07, and the Best Scientific Paper award at ICPR ’08.
Pedro F. Felzenszwalb received the BS degree in computer science from Cornell University in 1999. He received the PhD degree in computer science from the Massachusetts Institute of Technology (MIT) in 2003. After leaving MIT, he spent one year as a postdoctoral researcher at Cornell University. Currently he is an associate professor in the Department of Computer Science at the University of Chicago. His main research interests are in computer vision, geometric algorithms, and artificial intelligence.
Arthur Gretton received degrees in physics and systems engineering from the Australian National University in 1996 and 1998, respectively; and completed the PhD degree with the Signal Processing and Communications Laboratory and Microsoft Research at the University of Cambridge in 2003. He has been a project scientist with the Machine Learning Department at Carnegie Mellon University since February 2009 and is affiliated as a research scientist with the Max Planck Institute for Biological Cybernetics, where he has worked since September 2002. His research interests include machine learning, kernel methods, statistical learning theory, nonparametric hypothesis testing, blind source separation, Gaussian processes, and nonparametric techniques for neural data analysis.
AleÅ¡ Leonardis received the PhD degree in computer science from the University of Ljubljana, Slovenia. He is a full professor and the head of the Visual Cognitive Systems Laboratory of the Faculty of Computer and Information Science at the University of Ljubljana. He is also an adjunct professor on the Faculty of Computer Science at Graz University of Technology. From 1988-1991, he was a visiting researcher in the General Robotics and Active Sensory Perception Laboratory at the University of Pennsylvania. Between 1995 and 1997, he was a postdoctoral associate at the PRIP, Vienna University of Technology, Austria. He was also a visiting researcher and a visiting professor at the ETH, Switzerland, and at the Technische Fakultät der Friedrich-Alexander-Universität in Erlangen, Germany, respectively. He has published more than 150 papers in refereed journals and conferences and he coauthored the book Segmentation and Recovery of Superquadrics (Kluwer, 2000). He has served in various roles at major international conferences, including ICCV, ECCV, CVPR, ICPR, and he was a program cochair of ECCV ’06. He is on the editorial board of Pattern Recognition and the Springer Book Series, Computational Imaging and Vision. His research interests include object recognition and categorization, statistical visual learning, and biologically motivated vision. He has received several awards. In 2002, he coauthored a paper, “Multiple Eigenspaces,” which won the 29th Annual Pattern Recognition Society award. In 2004, he was awarded a prestigious national award for academic achievements. He is a member of the IEEE and a fellow of the IAPR.
Ravi Ramamoorthi received the BS and MS degrees from the California Institute of Technology in 1998 and the PhD degree from Stanford University in 2002. He is currently an acting associate professor of electrical engineering and computer science at the University of California, Berkeley. He moved to Berkeley in January 2009 from Columbia University, where he had been on the faculty of the Computer Science Department since Fall 2002. His research interests lie in many aspects of computer vision and computer graphics, including mathematical foundations of visual appearance, real-time photorealistic rendering, image-based and inverse rendering, and modeling lighting and reflectance in computer vision. In 2008, his work in computer vision was recognized with the Presidential Early Career Award for Scientists and Engineers “for investigating foundations of the visual appearance of objects and developing mathematical and computational models for recreating complex scenes for automated image understanding...” In 2007, he received the ACM SIGGRAPH Significant New Researcher Award in computer graphics for “his groundbreaking work on mathematical representations and computational models for the visual appearance of objects...” Earlier, he received the 2007 US Office of Naval Research Young Investigator Award and, in 2005, the Alfred P. Sloan Fellowship and the US National Science Foundation Career Award.
Charles V. Stewart received the BA degree in mathematical sciences from Williams College in 1982 and the MS and PhD degrees in computer science from the University of Wisconsin in 1985 and 1988, respectively. Currently, he is a professor in the Department of Computer Science at Rensselaer Polytechnic Institute, Troy, New York. He has done sabbaticals at the GE Center for Research and Development in Niskayuna, New York, and at the Johns Hopkins University. In 1999, together with Ali Can and Badrinath Roysam, he received the Best Paper Award at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). He was CVPR Local Arrangements Chair in 2003, Workshops Chair in 2006, and an Area Chair for 2008. He served on the editorial board of Image and Vision Computing. In 2006, he founded DualAlign LLC, where he is now Chief Scientist while on leave from Rensselaer. His research interests include computer vision, medical image analysis, and graphics, emphasizing image registration and three-dimensional modeling.
John Winn received the doctorate degree from the University of Cambridge, where he was supervised by Professor Chris Bishop and Professor David MacKay. He is a researcher at Microsoft Research Cambridge in the Machine Learning and Perception Group. His main research interests are machine learning, machine vision, especially object recognition, and bioinformatics. His work includes development of Variational Message Passing and he also cocreated, with Tom Minka, the Infer.NET framework for automatic inference. He was also a founder of Hypertag, a company which allows you to interact with advertisements using your mobile phone.
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