Isabelle Guyon

Dr. Guyon is co-inventor of the support vector machine (SVM) algorithm, and SVM-RFE feature selection, two machine learning methods essential for scientific prediction in biomedical informatics. These methods have been referenced in more than 10,000 papers. She has authored a highly cited (>2,000 citations) seminal paper on feature selection and has co-authored several books and organized workshops and competitions on feature selection and causal discovery. In the years immediately preceding her election to the College, she led a major initiative on data exchange, online experimentation, and causal discovery benchmarking called the Causality Workbench. Dr Guyon is among the most cited researchers in machine learning internationally, has developed original methods for biomedical informatics, and has applied them in ways that can significantly improve medical care. Her election to fellowship recognizes these sustained technical and professional achievements.