Welcome! This is the academic website of Jack O’Brien. I’m an applied statistician, data scientist, and an associate professor of mathematics at Bowdoin College. My research is on how mixture models and similar approaches can be used to analyze social science data like pottery sherds, election results, and tweets to create remarkably simple portraits of complex social phenomena. I’m also fascinated by housing dynamics.
Experience
- Associate Professor, Bowdoin College (2018-present)
- Senior Statistician, Wellcome Trust Centre for Human Genetics, University of Oxford (2010-2012)
- Research Associate in Statistical Genetics, University of Bristol (2008-2009)
Education
- BA, Pomona College (Mathematics)
- PhD, UCLA (Biomathematics)
As we confront the disaster of increasing authoritarianism and its computational and data-based implementation, I think it is incumbent upon us as quantitative scholars that we challenge ourselves to do the difficult work of re-imagining our disciplines freed from their associations with the surveillance state. The Just Mathematics Collective provides some much needed initiative in that direction.
Recent work
- (Dec 2025) Check out my recent(ish) paper using mixture models to map political ideology using election data: O’Brien. 2025. “A Bayesian mixture model captures temporal and spatial structure of voting blocs within longitudinal referendum data”. Currently in press in Political Science Research and Methods.
- (Dec 2025) My two honors students, Avery Cutler and Nathan Kellerman, made absolutely amazing mid-year presentations on their respective projects. Check out their projects here: [Avery’s on modeling eviction records in Boston] and Nathan’s work on a new EM algorithm for overdispersed count data.
- (July 2025) Very happy to see Assistant Professor of Physics Fe McBride’s paper, “A radio-quiet AGN as a candidate counterpart to neutrino event IceCube–200615A” (on which I made a very small assist) published in The Monthly Notices of the Royal Astronomical Society.