The Community for Technology Leaders

Introduction of New Associate Editors

Rama Chellappa
David J. Kriegman

Pages: p. 529

We are pleased to announce the appointments of Professors Joachim M. Buhmann and Yann LeCun; both are distinguished researchers in pattern recognition and statistical learning. Professor Buhmann will handle papers in statistical learning theory, data clustering and image segmentation. Professor LeCun will handle papers in theory and applications of pattern classification, machine learning, and digital libraries. Their brief biographies and photos appear below.

About the Authors

Bio Graphic
Joachim M. Buhmann received the PhD degree in theoretical physics from the Technical University of Munich, Munich, Germany, in 1988. His thesis explored methods to store and recognize visual patterns in artificial and biologically plausible neural networks. Afterward, he held postdoctoral and research faculty positions at the University of Southern California, Los Angeles, and the Lawrence Livermore National Laboratory, Livermore, California. From 1992-2003, he headed the Research Group on Computer Vision and Pattern Recognition, Computer Science Department, Rheinische Friedrich-Wilhelms-Universität Bonn, Germany. Currently, he is a professor in the Computer Science Department at the Institute of Computational Science of the Swiss Federal Institute of Technology (ETH Zurich). His research interests cover statistical learning theory and computational statistics with applications to image understanding and bioinformatics. Special research topics include exploratory data analysis and data mining, stochastic optimization, computer vision, remote sensing, and analysis of biological data. He has been a member of the Technical Committee of the German Pattern Recognition Society (DAGM) since 1995, which he headed from 1999-2003.
Bio Graphic
Yann LeCun received the Engineer Diploma degree from ESIEE, Paris in 1983 and the PhD degree in computer science from Université Curie, Paris in 1987. He is a professor of computer science with the Courant Institute of Mathematical Sciences at New York University (NYU). After a postdoctoral fellowship at the University of Toronto, Dr. LeCun joined the Adaptive Systems Research Department at AT&T Bell Laboratories in 1988. Following the AT&T/Lucent spin-off in 1996, he joined AT&T Labs-Research as head of the Image Processing Research Department. In 2002, he became a fellow at the NEC Research Institute in Princeton. He joined the NYU faculty in 2003. Dr. LeCun's research interests include computational and biological models of learning and perception, computer vision, robotics, information theory, data compression, digital libraries, and the physical basis of computation. Some of the methods and technologies he developed are in wide commercial use for pattern recognition applications, data mining systems, and digital libraries. His handwriting recognition systems are used by many banks to automate check processing, and his DjVu document image compression system is used by hundreds of online digital libraries around the world.
65 ms
(Ver 3.x)