Djamel Bouchaffra received his Ph.D. degree in computer science from University of Grenoble, France. He serves currently as an Associate Professor of computer science at the Department of Mathematics and Computer Science at GSU in Louisiana. He held a position of Research Scientist at the University of New York at Buffalo (Center of Excellence for Document Analysis and Recognition) and later took a position of Assistant Professor at Oakland University, Michigan. His field of research is pattern recognition, machine learning, computer vision, and artificial intelligence. He is currently working on the development of mathematical models that have the ability to (i) embed discrete structures into a Euclidean or a Riemannian space, (ii) merge topology with statistics, and (ii) use this fusion to perform adaptive classification of complex patterns. Professor Bouchaffra has introduced both the structural and the topological hidden Markov models as two novel paradigms that attempt to implement this fusion. He has written several papers in peer-reviewed conferences and premier journals such as IEEE TPAMI and Pattern Recognition Journal (http://www.djamel-bouchaffra.info). He was the Lead Guest Editor of a special issue in the journal of Pattern Recognition titled: Feature Extraction and Machine Learning for Robust Multimodal Biometrics published in March 2008 (vol. 41/3); he chaired several sessions in conferences. He is among the reviewer panel of some governmental funding agencies such as NASA (ADP Program: Data Analysis and Astrophysics) and EPSRC in the United Kingdom. He was one of the general chairs of the conference ICSIT'05. Professor Bouchaffra is an Editorial Board Member in several journals such as Journal of Pattern Recognition (Elsevier), Advances in Artificial Intelligence (Hindawi), and others. Dr. Bouchaffra is a Senior Member of the IEEE and a Member of the IEEE Computer Society.
Biography Updated on 27 January 2011