Machine learning focuses on the creation, characterization and development of algorithms that, when applied to data, allow us to understand their structure, make predictions and construct counterfactual analyses. This area of research is fundamental to applied statistics and data science and drives many of their recent advancements, including in artificial intelligence and large language models. Our faculty actively research methodological and computational approaches to machine learning, especially in high-dimensional data and data-intensive computing, to create new tools for scientific discovery. Through collaboration with researchers across campus, YSPH researchers apply these tools to genetics, clinical trials, neuroimaging and other areas of biomedicine.
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Associate Professor of Biostatistics; Affiliated Faculty, Yale Institute for Global Health
Associate Professor of Biostatistics
Associate Professor of Biostatistics and Associate Professor of Medicine (Cardiovascular Medicine)
Department Chair and Professor of Biostatistics
Assistant Professor of Biostatistics; Co-Training Director, Health Informatics MS
Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology; Co-Leader, Genomics, Genetics, & Epigenetics Research Program
Professor of Biostatistics
Professor of Biostatistics
Associate Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine); Director of Data Analysis and Bioinformatics Hub, The Center for Precision Pulmonary Medicine (P2MED); Assistant Professor, Biostatistics
Susan Dwight Bliss Professor of Biostatistics, Professor in the Child Study Center and Professor of Statistics and Data Science, Professor of Obstetrics, Gynecology, and Reproductive Sciences; Affiliated Faculty, Yale Institute for Global Health
Ira V. Hiscock Professor of Biostatistics, Professor of Genetics and Professor of Statistics and Data Science
Associate Professor of Biostatistics and Associate Professor of Biomedical Informatics & Data Science
Assistant Professor of Biostatistics
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