Emma Pierson

In January 2025 I will join the Berkeley EECS faculty, affiliated with the Berkeley AI Research Lab, Computational Precision Health, and the Center for Human-Compatible AI. I will be taking PhD students; please apply to Berkeley in Fall 2024 and mention my name in your application if you are interested in working with me. I am very lucky to get to work with many wonderful students and postdocs.

I develop data science and machine learning methods to study two broad areas: inequality and healthcare. For representative publications, please see my papers on inequality in pain (Nature Medicine, 2021); inequality in policing (Nature Human Behaviour, 2020); inequality in COVID-19 (Nature, 2021); segregation (Nature, 2023); and fair clinical prediction (New England Journal of Medicine, 2024). My work has been recognized by best paper awards at KDD and AISTATS, an NSF CAREER award, a Rhodes Scholarship, Hertz Fellowship, Rising Star in EECS, MIT Technology Review 35 Innovators Under 35, Forbes 30 Under 30 in Science, AI2050 Early Career Fellowship, and Samsung AI Researcher of the Year.

Previously, I was a senior researcher at Microsoft Research New England and a PhD student in Jure Leskovec's lab at Stanford. Before my PhD, I did a master's in statistics at Oxford, and before that I spent a year as a data scientist at 23andMe and Coursera. I write a statistics blog, Obsession with Regression, and have also written for The New York Times, FiveThirtyEight, The Atlantic, The Washington Post, Wired, Times Higher Education, and various other publications.