PhD, Universit of Aix-en-Provence
Memory and Cognition, Quantitative Models, Neuroimaging, Genomics
Hervé Abdi received an MS in Psychology from the University of Franche-Comté (France) in 1975, an MS (D.E.A.) in Economics from the University of Clermond-Ferrand (France) in 1976, an MS (D.E.A.) in Neurology from the University Louis Pasteur in Strasbourg (France) in 1977, and a PhD in Mathematical Psychology from the University of Aix-en-Provence (France) in 1980.
He was an assistant professor in the University of Franche-Comté (France) in 1979, an associate professor in the University of Bourgogne at Dijon (France) in 1983, a full professor in the University of Bourgogne at Dijon (France) in 1988. He is currently a full professor in the School of Behavioral and Brain Sciences at The University of Texas at Dallas and an adjunct professor of Radiology at The University of Texas Southwestern Medical Center at Dallas.
Dr. Abdi was a Fullbright scholar and visiting associate professor of Cognitive and Linguistic Sciences at Brown University in 1986 and 1987; he has been, also, a visiting professor at the University of Geneva (Switzerland), Chuo University (Japan), Université de Dijon (France), Université de la Sorbonne (Paris), the "Conservatoire Nationale des Art et Métiers" (Paris) and the Rotman institute (Canada).
My research is organized around three areas: psychology of memory, neural networks, and statistics. The psychology of memory research is mainly directed toward the modeling of long term semantic memory (e.g., scripts, schema, concepts) and memory for faces. The neural networks research is directed at finding a generalization of auto-associative networks and to the analysis of the statistical properties of connectionist models. My work with statistics is oriented towards two domains: analysis of variance (experimental design) and analysis of qualitative data (correspondence analysis, additive tree analysis).
Abdi, H., Williams, L.J., & Valentin, D. (2013). Multiple factor analysis: Principal component analysis for multi-table and multi-block data sets. Wiley Interdisciplinary Reviews: Computational Statistics, 5, 149-179.
Abdi, H., Williams, L.J., Beaton, D., Posamentier, M., Harris, T.S., Krishnan, A., & Devous, M.D. (2012). Analysis of regional cerebral blood flow data to discriminate among Alzheimer's disease, fronto-temporal dementia, and elderly controls: A multi-block barycentric discriminant analysis (MUBADA) methodology. Journal of Alzheimer Disease, 31, s189-s201.
Abdi, H., Williams, L.J., Connolly, A.C., Gobbini, M.I., Dunlop, J.P., & Haxby, J.V. (2012). Multiple Subject Barycentric Discriminant Analysis (MUSUBADA): How to assign scans to categories without using spatial normalization. Computational and Mathematical Methods in Medicine, 2012, 1-15. doi:10.1155/2012/634165