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Alex Bloemendal is a senior machine learning scientist and institute scientist at the Ó³»­´«Ã½ of MIT and Harvard. Joining the Translational Genomics Group in the Program for Medical and Population Genetics from the Data Sciences Platform, he leads and advises interdisciplinary and external collaborations that bring state-of-the-art computational tools to bear on the problems of translational genomics and genomic medicine, especially the diagnosis of rare disease. Previously, as a member of the Neale and Lander Labs, Bloemendal helped develop methods for analyzing human genetic and other large-scale biological data toward a better understanding of the mechanisms underlying common and complex disease, initially co-founding the Hail project for scalable genomic analysis. Bloemendal also co-founded and co-chaired the Ó³»­´«Ã½â€™s Models, Inference & Algorithms initiative, a widely attended seminar series and community to foster learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science.

Bloemendal was previously a Simons Fellow in the Department of Mathematics and a research scientist in the Program for Evolutionary Dynamics at Harvard University. His research in probability and random matrix theory focused on questions around signal and noise in high-dimensional data; he proved a conjecture with wide-reaching applications in fields including population genetics. Bloemendal also earned a teaching award for an advanced course on probability.

Bloemendal received an Hon. B.Sc., M.Sc., and Ph.D. in mathematics from the University of Toronto.