Jasjeet S. Sekhon
NationalityAmerican and Canadian
Alma materUniversity of British Columbia (B.A.), Cornell University (M.A., Ph.D.)
Scientific career
FieldsStatistics, Data Science, Machine Learning, Causal Inference, Political Science
InstitutionsHarvard University
University of California, Berkeley
Yale University
Doctoral advisorWalter Mebane

Jasjeet "Jas" Singh Sekhon is a data scientist, political scientist, and statistician at Yale University. Sekhon is the Eugene Meyer Professor at Yale University,[1] a fellow of the American Statistical Association,[2] and a fellow of the Society for Political Methodology.[3] Sekhon's primary research interests lie in causal inference, machine learning, and their intersection.[4] He has also published research on their application in various fields including voting behavior, online experimentation, epidemiology, and medicine.

Biography

Sekhon graduated with a B.A. from the University of British Columbia. In 1999, he earned a Ph.D. at Cornell University.[3][5]

Sekhon's career in academia began in 1999, when he became an assistant professor at Harvard University. He stayed at Harvard until 2005 when he moved to UC Berkeley. At Berkeley, he was appointed as the Robson Professor of Political Science and Statistics in 2014.[6] In 2019, he accepted a non-academic position as Head of Advanced Data Science at Bridgewater Associates, and in 2020 left Berkeley to join Yale University, where he was appointed Meyer Professor of Political Science and Statistics and Data Science in 2021.[7] He was named a fellow of the Society for Political Methodology in 2019[3] and a fellow of the American Statistical Association in 2021.[2]

Sekhon has authored or co-authored dozens of journal articles and several widely used R packages. The topics of his scholarship include experimental research methods, machine learning for estimating causal effects, election fraud, and matching. His research has been widely cited.[8]

Research

Sekhon is best known for his research in causal inference and machine learning. His early research on causal inference focused on the role of matching, but he later wrote an article pointing out that matching is unable to address many of the problems (particularly the selection on observables assumption) that its proponents assume. Nevertheless, his Genetic Matching algorithm remains one of his most highly cited articles.[8] As of 2021, his research focuses on developing interpretable and credible machine learning methods for estimating causal relationships.[5]

One of Sekhon's first publications, a journal article in Digestive Diseases and Sciences, presented a novel treatment, glucocorticoid, for a rare disease that he suffered. Sekhon himself was the first case described in the article.[9]

Selected publications

References

  1. ↑ "Jasjeet Sekhon". Department of Statistics and Data Science. Yale University. Retrieved 4 June 2021.
  2. 1 2 "Jas Sekhon Selected as a Fellow of the American Statistical Association". Department of Statistics and Data Science. Yale University. Retrieved 4 June 2021.
  3. 1 2 3 "Fellows". Cambridge University Press. Society for Political Methodology. Retrieved 4 June 2021.
  4. ↑ "Jasjeet Sekhon". Jasjeet Sekhon. Retrieved 3 June 2021.
  5. 1 2 "Jasjeet Sekhon". New Ladder Faculty (2020-2021). Yale University. Retrieved 4 June 2021.
  6. ↑ "Curriculum Vitae" (PDF).
  7. ↑ "Sekhon named Meyer Professor of Political Science and Statistics and Data". YaleNews.
  8. 1 2 ""Jasjeet S. Sekhon - Google Scholar"". Jasjeet S. Sekhon - Google Scholar. Google Scholar. Retrieved 28 November 2021.
  9. ↑ Sekhon, Jasjeet; Chung, Raymond; Epstein, Mark; Kaplan, Marshal (2005). "Steroid-Responsive (Autoimmune?) Sclerosing Cholangitis". Digestive Diseases and Sciences. 50 (10): 1838–1843. doi:10.1007/s10620-005-2948-3. PMID 16187184. S2CID 15494269.
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