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Guy Wolf is an Associate Professor in the Department of Mathematics and Statistics at the Université de Montréal. His research interests lie at the intersection of machine learning, data science and applied mathematics. He is particularly interested in data mining methods that use manifold learning and deep geometric learning, as well as applications for exploratory analysis of biomedical data.
His research focuses on exploratory data analysis, with applications in bioinformatics. His approaches are multidisciplinary and combine together machine learning, signal processing, and applied math tools. In particular, his recent works use a combination of diffusion geometries and deep learning to find emergent patterns, dynamics, and structure in big high dimensional data (e.g., in single-cell genomics and proteomics).
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