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Scientific team
Scientific team
The hosting team for this project is the AI-DSCy team (Artificial Intelligence for Data Science and Cybersecurity), led by Pr. M. Nadif, which is part of the Centre Borelli (Université de Paris, Centre Borelli UMR 9010), within the Department of Sciences Fondamentales et Biomédicales at Université de Paris. Centre Borelli is carrying out theoretical and applied research in the areas of mathematics, computer science, machine learning, modeling of complex biophysics systems and neuroscience. The AI-DSCy team research projects focus on latent block models, tri-factorisation, spectral co-clustering and original works consisting in embedding the co-clustering in ensemble methods.
GePhEx partners, who are also member of the AI-DSCy team, share the common objective of developing new learning methods and user-friendly software that can integrate various types of omics data to identify environmental exposures, disease symptoms and altered genes in human complex diseases. The members of AI-DSCy contributing to this project include Pr. M. Nadif, Dr. L. Labiod, and Dr. F. Role, who possess the adequate complementary skills to answer the pluridisciplinary aspects of GePhEx. They have a strong expertise in unsupervised and supervised learning as well as text mining for large amounts of data. They also developed visualization methods for document co-clusters and other text mining analysis outputs that allow graphical model based representations.
Project Coordinator / Dr. Séverine Affeldt / Université de Paris, Centre Borelli UMR 9010
Séverine Affeldt is Associate Professor of Computer Science at the Université de Paris (Paris 5) and has an expertise in unsupervised learning for large amounts of data. She obtained her Master degree in Computer Science in 2011 from the Université Pierre et Marie Curie (Paris 6) and completed her Ph.D. in Computer Science at the same university in 2015. She is now member of the Machine Learning for Data Science team at the Université de Paris. Currently, her research focuses on deep clustering, data mining and modeling of multi-view data.
Dr. Lazhar Labiod / Université de Paris, Centre Borelli UMR 9010
Lazhar Labiod is a researcher in data mining and statistical learning. He obtained his Master degree in Statistics in 2003 from the Université Pierre et Marie Curie. He obtained his Ph.D. in 2008 in applied Mathematics and Statistics from the Université Pierre et Marie Curie. He is now Associate Professor at the Université de Paris and member of the Machine Learning for Data Science team. Currently, his research focuses on co-clustering, approximation and matrix decomposition and modeling of multi-view data.
Dr. François Role / Université de Paris, Centre Borelli UMR 9010
François Role is a senior lecturer at the Université de Paris. His research interests include text mining techniques, knowledge extraction, graph-based summarization and cluster labeling. He has a strong background in NLP and information extraction from unstructured information sources.
Pr. Mohamed Nadif / Université de Paris, Centre Borelli UMR 9010
Mohamed Nadif is a full Professor at the Université de Paris. He leads the research activities of the Machine Learning for Data Science team and teaches course covering various topics, including data science, machine learning and multivariate data analysis. His current research interests include cluster analysis, co-clustering, data analysis, visualization, factorization and latent block models.
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