Adam Hearn

Data Scientist, Researcher, Higher-Education Advocate

American Institutes for Research


I am a current Data Scientist Associate at the American Institutes for Research. I hold an. M.S. in Data Science for Public Policy from Georgetown University and a BA in Economics from Rhodes College. I am skilled in computational social science research, machine learning, causal inference, data visualization, and higher-ed data governance and analytics in enrollment management and institutional research.

Experienced in the postsecondary sector through appointments at SHEEO, AIR, College Transitions. Addititionally, I previously served as Director of Data Analytics and Institutional Research at Franklin College in Indiana.

My mission is to leverage my data science and technical background for the public good, and increase postsecondary attainment as a result.

CV can be downloaded here.


  • Computational Social Science Research
  • Machine Learning (Supervised and Unsupervised)
  • Higher Education Access/Choice


  • MS in Data Science for Public Policy, 2021

    Georgetown University

  • BA in Economics, 2019

    Rhodes College










Data Scientist Associate

American Institutes for Research

Jun 2022 – Present Arlington, VA
The American Institutes for Research is a behavioral and social science research, evaluation and technical assistance organization whose mission is to generate and use rigorous evidence that contributes to a better, more equitable world.

Director of Institutional Research & Data Analytics

Franklin College

Feb 2021 – Jun 2022 Franklin, IN
Franklin College is a residential, open-access liberal arts institution located 20 minutes south of Indianapolis. A Franklin College education fosters independent thinking, innovation, leadership, and action for ever-changing professions and a globally connected world.

Data Scientist & Database Administrator

College Transitions, LLC

May 2018 – Present Charlotte, NC
A team of consultants, researchers, and former admissions officers, College Transitions offers a data-driven program of services that helps students identify good-fit schools, maximize their admission prospects, and make the most of their college investment.


The Generalized Synthetic Control Method: A Powerful ML Algorithm to Produce Counterfactual Estimates for Experimental Data

This post will cover the Generalized Synthetic Control method, a ML algorithm that is lesser known within Data Science circles.



Do institutions serve their geographic constituents? Evidence from student migratory patterns

This RShiny web-app provides a resource for higher-ed stakeholders and researchers to investigate migration patterns of postsecondary learners.

The Higher-Ed Coronavirus Response in the Public Sector

Using data form the College Crisis Initiative, this project discusses the usage of dimensionality reduction techniques and feature importance algorithms to analyze fall re-opening plans.

Isolating the Mechanisms Behind the Test-Optional Admissions Policy

Using machine learning classification algorithms, this paper reveals varying motives for postsecondary institutions adopting the test-optional admissions policy.

Everyone Wants to Win: Even the Admissions Officers

Winner of the 2019 Rhodes College Lynn Nettleton Prize in Economics, this paper uses fixed-effects regression models to study the symbiotic relationship of collegiate athletics and institutional research.

Using NCAA Track Data as a Predictor for Race Times

NCAA Track & Field results can be mined to create an ecosystem of robust running data.


Picks and algorithms


NBA Picks

Using data form the College Crisis Initiative, this project discusses the usage of dimensionality reduction techniques and feature …