Djamel Bouchaffra
Oakland University, USA
Djamel Bouchaffra is a Professor of computer science at Oakland University. He was the recipient of both the 2004 Oakland University Teaching Excellence Award and the School of Engineering Teaching Award. This recognition acknowledges the genuine admiration of his students and colleagues for his superior level of professionalism in teaching. His field of research is in pattern recognition, machine learning, computer vision, and artificial intelligence. His goal is to merge statistics and structure together within a single Bayesian framework, and to use this fusion to perform classification of complex patterns. He introduced both the structural and the topological hidden Markov models that implement this fusion. His areas of application include bioinformatics, biometrics, speech, handwriting recognition, language modeling, and data mining. He has written several papers in peer-reviewed conferences and premier journals. He chaired several conference sessions; he was one of the general chairs of the conference ICSIT'05. He is a regular reviewer for some funding agencies and journals such as IEEE TPAMI, TNN, TKDE, and Image Processing. He is a Guest Editor of the Pattern Recognition special issue titled: “Feature Generation and Machine Learning for Robust Multimodal Biometrics” that will be published in January 2008. Dr. Bouchaffra is a Member of the editorial board of the Journal of Pattern Recognition (Elsevier), an associate editor for the Journal Advances in Artificial Intelligence (Hindawi) and the Journal of Engineering Letters (International Association of Engineers). Dr. Bouchaffra is a Senior Member of the IEEE, a Member of the IEEE Computer Society, and the Vice Chair of the IEEE/SEM chapter V.
Biography Updated on 1 August 2007
Personal Home Page
http://www.oakland.edu/~bouchaff
Articles in Scholarly Journals [Incomplete List]
- A Statistical Multiresolution Approach for Face Recognition Using Structural Hidden Markov Models
EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 675787, 13 pages, 2008 - STRUCTURAL HIDDEN MARKOV MODELS BASED ON STOCHASTIC CONTEXT-FREE GRAMMARS
Control and Intelligent Systems, vol. 35, no. 3, 2007 - Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs
Data Mining and Knowledge Discovery, vol. 12, no. 1, pp. 79–96, 2006 - Probabilistic logic with minimum perplexity: Application to language modeling
Pattern Recognition, vol. 38, no. 8, pp. 1307–1315, 2005 - Genetic-Based EM Algorithm for Learning Gaussian Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1344–1348, 2005 - Introduction of Logic in Language Modelling: The Minimum Perplexity Criterion
International Journal of Robotics and Automation, vol. 20, no. 3, 2005 - Postprocessing of recognized strings using nonstationary Markovian models
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 990–999, 1999 - A methodology for mapping scores to probabilities
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 9, pp. 923–927, 1999 - Incorporating diverse information sources in handwriting recognition postprocessing
International Journal of Imaging Systems and Technology, vol. 7, no. 4, pp. 320–329, 1996