Lester Mackey. Lester Mackey is an American computer scientist and  statistician. He is a principal researcher at Microsoft Research and an adjunct professor at Stanford University. Mackey develops machine learning methods, models, and theory for large-scale learning tasks driven by applications from climate forecasting, healthcare, and the social good. He was named a 2023 MacArthur Fellow.

Early life and education 
Mackey grew up on Long Island. He has said that, as a teenager, the Ross Mathematics Program in number theory introduced him to proof-based mathematics, where he learned about induction and rigorous proof. He got his first taste of academic research at the Research Science Institute. He joined Princeton University as an undergraduate student, where he earned his BSE in Computer Science. There he conducted research with Maria Klawe and David Walker. Mackey was a graduate student at the University of California, Berkeley, where he earned a PhD in Computer Science (2012) and an MA in Statistics (2011). At Berkeley, his dissertation, advised by Michael I. Jordan, included work on sparse principal components analysis (PCA) for gene expression modeling, low-rank matrix completion for recommender systems, robust matrix factorization for video surveillance, and concentration inequalities for matrices. After Berkeley, he joined Stanford University, first as a postdoctoral fellow working with Emmanuel Candès and then as an assistant professor of statistics and, by courtesy, computer science. At Stanford, he created the Statistics for Social Good working group.

Research and career 
In 2016, Mackey joined Microsoft Research as a researcher and was appointed as an adjunct professor at Stanford University. He was made a principal researcher in 2019.

Mackey's early work developed a method to predict progression rates of people with ALS. He used the PRO-ACT database of clinical trial data and Bayesian inference to predict disease prognosis. He has also developed machine learning models for subseasonal climate and weather forecasting, to more accurately predict temperature and precipitation 2-6 weeks in advance. His models outperform the operational, physics-based dynamical models used by the United States Bureau of Reclamation.

Awards and honors 
 2003 Intel Science Talent Search 6th Place
 Namesake of minor planet 15093 Lestermackey
 2006 Barry M. Goldwater Scholarship
 2007 Computing Research Association Outstanding Undergraduate Award Winner
 2007 Moses Taylor Pyne Honor Prize
 2009 Second Place in the $1 million Netflix Prize competition for collaborative filtering
 2010 Best Student Paper Award, International Conference on Machine Learning
 2012 First Place in the ALS Prediction Prize4Life Challenge for predicting Lou Gehrig's disease progression
 2019 Winner of U.S. Bureau of Reclamation's Subseasonal Climate Forecast Rodeo
 2022 Elected to the Committee of Presidents of Statistical Societies Leadership Academy
 2022 Outstanding Paper Award, NeurIPS
 2023 Ethel Newbold Prize
 2023 Elected Fellow of the Institute of Mathematical Statistics
 2023 MacArthur Fellowship
 2024 Elected Fellow of the American Statistical Association

Selected publications

References 

Living people
Year of birth missing (living people)
People from Long Island
Princeton University alumni
University of California, Berkeley alumni
Microsoft employees
MacArthur Fellows
Statisticians
American statisticians
African-American statisticians
Computer scientists
American computer scientists
African-American computer scientists
Stanford University Department of Statistics faculty
Fellows of the American Statistical Association