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Introduction of New Associate Editors

David J.

Pages: pp. 1349-1350

We are pleased to announce that Graham D. Finlayson, Zoubin Ghahramani, John Oliensis, and Bernhard Schölkopf have joined TPAMI as Associate Editors. Their addition greatly enhances the depth of our editorial board in computer vision and machine learning. Graham D. Finlayson will handle papers in physics-based vision and, in particular, colour processing ("u" included by way of point of origin), photometric methods in computer vision, and shadowing. John Oliensis will handle papers on structure from motion, shape from X, illumination, statistical methods, recognition, perceptual organization/grouping/segmentation, early vision, tracking, and shape representation. Zoubin Ghahramani will be considering manuscripts in machine learning and, particularly, statistical machine learning, graphical models, Bayesian methods, Gaussian processes, semisupervised learning, sampling methods, hidden Markov models, and variational methods. Bernhard Schölkopf will oversee papers in complementary areas of machine learning, especially kernel methods, support vector machines, dimensionality reduction, semisupervised learning, and manifold learning. Their brief biographies appear below.

Welcome aboard. We look forward to working with you.

David J. Kriegman, Editor-in-Chief

David Fleet, Associate-Editor-in-Chief

About the Authors

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Graham D. Finlayson received the BSc degree in computer science (with honors) from the University of Strathclyde, Glasgow, Scotland, in 1989. He received the MSc and PhD degrees from Simon Fraser University, Vancouver, Canada, respectively, in 1992 and 1995. His PhD dissertation was awarded a Dean's medal for academic excellence. From 1995 to 1997, he was a lecturer in the Department of Computer Science at the University of York in the United Kingdom. In 1997, he was appointed to a readership at the University of Derby, where he was a founding member of the Colour & Imaging Institute. In 1999, he left Derby to become a full professor in the School of Computing Sciences at the University of East Anglia. Professor Finlayson is interested in how color can be used to solve problems in computer vision and allied disciplines such as image processing and digital photography. He has made many contributions toward solving the color constancy problem (removing color bias due to illumination from images) and his algorithms have been implemented in commercial cameras. His current research interests include dynamic range compression, the automated removal of shadows in images, photometric invariance, and the application of computational techniques to the understanding of human vision.
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Zoubin Ghahramani received the PhD degree from the Massachusetts Institute of Technology in 1995, working with Michael Jordan. From 1995-1998, he was with the University of Toronto as an ITRC Postdoctoral Fellow with Geoffrey Hinton in the Artificial Intelligence Lab of the Department of Computer Science. Since 1998, he has been with the Gatsby Computational Neuroscience Unit at University College London, where he is currently a reader in machine learning and, since 2002, he has held an appointment as an associate research professor in the School of Computer Science at Carnegie Mellon University. His current research interests include Bayesian approaches to machine learning, artificial intelligence, statistics, and bioinformatics. He is on the editorial boards of the Journal of Machine Learning Research, Machine Learning, and Bayesian Analysis. He has served in various roles in the organization of the AISTATS, NIPS, ICML, and UAI conferences.
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John Oliensis received the PhD degree in theoretical particles physics from the University of Chicago and pursued research in physics at Princeton University, the Fermi National Accelerator Laboratory, and the Argonne National Laboratory. He began research in computer vision in 1988, joining the University of Massachusetts at Amherst and becoming a member of the research faculty there. He was a research scientist at the NEC Research Institute from 1994 to 2003 and, since 2003, has been an associate professor in the Computer Science Department of the Stevens Institute of Technology. At the University of Massachusetts, he solved the classical problem of shape from shading. At NEC, he organized three workshops which brought together researchers in computer vision, human vision, neuroscience, and learning, and he carried out research on structure from motion and human vision. His current interests include structure from motion, perceptual organization, control strategies for visual processing, object recognition, and human vision.
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Bernhard Schölkopf received degrees in mathematics (University of London, 1992) and physics (Eberhard-Karls-Universität Tübingen, 1994), and the doctorate degree in computer science (Technical University Berlin, 1997). He won the Lionel Cooper Memorial Prize of the University of London and the annual dissertation prize of the German Association for Computer Science (GI). He has done research at AT&T Bell Labs, GMD FIRST, Berlin, the Australian National University, Canberra, and at Microsoft Research Cambridge, United Kingdom. He has taught at Humboldt University and the Technical University Berlin. In July 2001, he was elected a scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in October 2002, he was appointed an honorary professor for machine learning at the Technical University Berlin.
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