Issue No. 10 - October (2007 vol. 29)
All good things must come to an end and, so, we must express our thanks to Kostas Daniilidis, Glenn Healey, Reinhard Klette, Ludmila I. Kuncheva, and Harry Shum, who are retiring as Associate Editors from the IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI). Each of these editors juggles many responsibilities and commitments and, so, we greatly value the generosity of their time and dedication to TPAMI. We're confident that they will find a good way to use a bit more free time.
We are pleased to announce that Professor Jana Kosecka, Dr. Neil Lawrence, Professor Daniel D. Lee, and Professor A.N. Rajagopalan have joined TPAMI's editorial board. Jana Kosecka will handle papers on structure from motion, robust estimation, scene representations, scene parsing, object recognition, feature selection, and visual navigation and localization. Neil Lawrence will cover papers in probabilistic approaches to machine learning, and their application to vision and robotics. Daniel D. Lee will be responsible for submissions on machine learning and robotics. A.N. Rajagopalan will oversee papers on shape from focus, image restoration, superresolution, face detection and recognition, locating and tracking people, gait recognition, Markov random fields, particle filters, and statistical learning. Their brief biographies are below.
Welcome to TPAMI's editorial board!
David J. Kriegman, Editor-in-Chief
David Fleet, Associate Editor-in-Chief
Jana Kosecka recieved the MSE degree in electrical engineering and computer science from the Slovak Technical University and the PhD degree in computer science from the University of Pennsylvania in 1996. She is an associate professor in the Department of Computer Science at George Mason University. From 1996 to 1999, she was a postdoctoral fellow in the Electrical Engineering and Computer Science Department at the University of California, Berkeley. She is the corecipient of the David Marr prize and received the US National Science Foundation CAREER Award. She is a member of the editorial board of the International Journal of Computer Vision and is a former associate editor of the IEEE Transactions on Robotics. Her general research interests are in computer vision and robotics. In particular, she is interested in "seeing" systems engaged in autonomous tasks, acquisition of static and dynamic models of environments by means of visual sensing, navigation, scene and object recognition, and human-computer interaction.
Neil Lawrence received the bachelor's degree in mechanical engineering from the University of Southampton in 1994. Following a period as a field engineer on oil rigs in the North Sea, he returned to academia to complete the PhD degree in 2000 at the Computer Lab at 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 a senior lecturer in 2005. In January 2007, he accepted a postition as a senior research fellow in the School of Computer Science at the University of Manchester, where he works in the Machine Learning and Optimisation Research Group. His main research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application in areas such as bioinformatics, speech, vision, and graphics. He has served on the program committees of several international conferences and was an area chair for the NIPS conference in 2005 and 2006.
Daniel D. Lee received the BA degree in physics from Harvard University in 1990 and the PhD degree in condensed matter physics from the Massachusetts Institute of Technology in 1995. He is currently an associate professor of electrical and systems engineering at the University of Pennsylvania, with a secondary appointment in the Department of Bioengineering. He was a researcher at Bell Laboratories, Lucent Technologies, from 1995-2001 in the Theoretical Physics and Biological Computation Departments. His research focuses on understanding the general principles that biological systems use to process and organize information and on applying that knowledge to building better artificial sensorimotor systems.
A.N. Rajagopalan received the PhD degree in electrical engineering from the Indian Institute of Technology, Bombay, in 1998. His thesis examined recovery of depth from defocused images. He was the first to model space-variant blur by a Markov random field, an idea that greatly improved the accuracy of depth from defocus technique and fueled research in motion-free superresolution of depth maps. During the summer of 1998, he was a visiting scientist at the Image Communication Lab at the University of Erlangen, Germany. He was an assistant research scientist at the Center for Automation Research at the University of Maryland, College Park, between 1998 and 2000. He joined the Indian Institute of Technology, Madras in 2000 and is currently an associate professor in the Department of Electrical Engineering. He held visiting positions at the Center for Automation Research at the University of Maryland in 2002 and 2005. He has served as a committee member for many computer vision conferences. His research interests include depth from defocus, nonlinear image restoration, shape from focus, superresolution, face detection and recognition, and higher-order statistical learning. He has published more than 80 peer reviewed journal and conference papers. He is a coauthor of the book Depth from Defocus: A Real Aperture Imaging Approach (Springer). He was awarded a Humboldt Research Fellowship in 2007 by the Alexander von Humboldt Foundation, Germany.
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