Issue No. 05 - May (2011 vol. 33)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.60
We are happy to announce the appointment to the TPAMI Editorial Board of Shai Avidan, Chris Bregler, Christoph Lampert, Carsten Rother and Yoram Singer. They will be handling a broad range of papers, as usual, but their emphasis will be as follows: Professor Avidan, object tracking from video and 3D modeling; Professor Bregler, motion tracking and vision for graphics; Professor Lampert, machine learning and computer vision; Doctor Rother, discrete optimization and vision for graphics; Doctor Singer, machine learning for massive data sets.
Brief biographies of these distinguished additions to the editorial board appear below. Welcome aboard, and thank you in advance for all of your hard work!
Since Editorial Board members serve a limited term under IEEE policy, we also have to announce the departure of Lèon Bottou, Olivier Chapelle, Frank Dellaert, Wolfgang Förstner, Fredrik Kahl, Stan Z. Li, Michael Lindenbaum, Yi Ma, Petros Maragos, Aleix Martinez, Lawrence O’Gorman, Marcello Pelillo, Patrick Perez, Yoichi Sato, Eric Saund, and Stan Sclaroff. Their service to the journal and the community are greatly appreciated by all of us.
Ramin Zabih, Editor-in-Chief
Zoubin Ghahramani, Associate Editor-in-Chief
Sing Bing Kang, Associate Editor-in-Chief
Jiri Matas, Associate Editor-in-Chief
Shai Avidan received the PhD degree from the School of Computer Science at the Hebrew University, Jerusalem, Israel, in 1999, and is now a faculty member at the School of Electrical Engineering at Tel-Aviv University, Israel. He has published extensively in the fields of object tracking in video sequences and 3D object modeling from images. Recently, he has been working on Internet vision applications such as privacy preserving image analysis, distributed algorithms for image analysis, and media retargeting, the problem of properly fitting images and video to displays of various size. Dr. Avidan was an area chair for ICCV ’07, CVPR ’08 and CVPR ’09, as well as SIGGRAPH ’09 and SIGGRAPH ’10. In addition, he was a program chair for several workshops, including the Workshop on Privacy Research in Vision held in conjunction with CVPR ’06, and the First Workshop on Internet Vision held in conjunction with CVPR ’08. Recently, he was a guest coeditor of a special issue of the IEEE on Internet Vision.
Chris Bregler received the MS and PhD degrees in computer science from the University of California, Berkeley, in 1995 and 1998 and the Diplom from Karlsruhe University in 1993. He is an associate professor of computer science at New York University’s (NYU) Courant Institute. Prior to joining NYU he was on the faculty at Stanford University and worked for several companies, including Hewlett Packard, Interval, Disney Feature Animation, and LucasFilm's ILM. He founded the Stanford Movement Group and the NYU Movement Group, which does research in vision and graphics with a focus on motion capture, animation, interactive media, and applications to entertainment, art, and medicine. This has resulted in numerous publications, patents, and awards from the US National Science Foundation, Sloan Foundation, Packard Foundation, US Office of Naval Research, Electronic Arts, Microsoft, and other sources. He was named Stanford’s Joyce Faculty Fellow and Terman Fellow in 1999. He received the Olympus Prize for achievements in computer vision and AI in 2002, and was named a Sloan Research Fellow in 2003. He was the chair for the SIGGRAPH ’04 Electronic Theater and Computer Animation Festival. At CVPR ’08 he was awarded the IEEE Longuet-Higgins Prize for “Fundamental Contributions in Computer Vision that have withstood the test of time.”
Christoph Lampert received the PhD degree summa cum laude in 2003 from the University of Bonn after studying mathematics at the University of Bonn and the Chalmers University of Technology in Gothenburg. From February 2004 to January 2007, he held a position as a senior researcher at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern and interned for three month at Google Inc in Mountain View, California. In February 2007, he joined the Max Planck Institute for Biological Cybernetics at Tuebingen as leader of the computer vision research group in the Department of Empirical Inference. In April 2010, he was appointed an assistant professor at the Institute of Science and Technology Austria (IST Austria), where he heads a research group for computer vision and machine learning. He has received international and national awards for his work on efficient object localization (CVPR ’08), structured regression training (ECCV ’08), and object classification using multiclass contect (DAGM ’08). His research interests lie in the interface between computer vision and machine learning, in particular in structured prediction and attribute-enabled image representations.
Carsten Rother received the Diploma degree with distinction in 1999 fromthe University of Karlsruhe, Germany. He received the PhD degree from the Royal Institute of Technology Stockholm, Sweden, supervised by Stefan Carlsson and Jan-Olof Eklundh. His thesis was nominated for the Best Nordic Thesis Award 2003-2004, as one out of two candidates from Sweden. Since 2003, he has been a researcher at Microsoft Research Cambridge, United Kingdom, and part of the machine learning and perception group. He supervises several PhD students and frequently gives invited talks and tutorials and organizes workshops. He won the best paper honorable mention award at CVPR ’05, and he was awarded the DAGM Olympus prize in 2009. He serves on the program committee of major conferences (e.g., SIGGRAPH, ICCV, ECCV, CVPR, NIPS). His research interests are in the field of Markov random fields for computer vision, discrete pptimization, and vision for graphics. He has published more than 20 high impact papers in international conferences and journals, and he is editing an upcoming book on advances in Markov random fields for vision and image processing (MIT Press). His work on image segmentation, starting with the GrabCut article in Siggraph ’04, has considerably influenced this research field, and currently has close to 700 citations. This work is also part of Microsoft Office 2010, and therefore probably one of most used vision technologies world-wide. He also designed the Microsoft Research product AutoCollage.
Yoram Singer is a senior research scientist at Google. His work focuses on the design, analysis, and implementation of machine learning algorithms for massive and high-dimensional data sets. Prior to his position at Google he was an associate professor at the Hebrew University, Jerusalem, Israel, and a member of the technical staff at AT&T Research (formerly AT&T Bell Labs). He served as an editor of the Machine Learning Journal. He currently serves as an associate editor of the Journal of Machine Learning Research and on the editorial board of IEEE Signal Processing Magazine. He cochaired the 17th Annual Conference on Learning Theory (COLT ’04) and the 21st Annual Conference on Neural Information Processing Systems (NIPS ’07).
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