I’m a Senior Data Scientist at Code for America! My research interests lie within computational social science. In prior work, I’ve measured the structural factors that drive a lack of diversity in science and highlighted their consequences. Broadly I’m interested in applying methods from causal inference and network science, joining surveys with big data, and studying fairness and social inequality by building systems. You can read about some other projects I have worked on here. Please reach out if you’d like to collaborate!
I earned my PhD in Computer Science at University of Colorado, Boulder, where I was a member of Aaron Clauset’s group. My research has been published in EPJ Data Science, PNAS, Science Advances, and Nature Human Behavior, and covered by outlets such as the Washington Post, Scientific American, and Forbes. I was fortunate to be supported throughout graduate school by the NSF GRFP. Prior to graduate school, I studied physics at Reed College. When I’m not at work, I like riding my bike and trying new recipes. My preferred pronouns are she/her.
JUN 2023 • You can learn more about the work I’ve been doing in Connecticut to help folks renew their SNAP benefits on Bloomberg, and in Minnesota to automatically renew Medicaid recipients’ health care benefits on Slate.
JAN 2023 • New year, new job! Starting a new role at Code for America as a Senior Data Scientist.
SEP 2022 • Promoted to Senior DS at Twitter!
AUG 2022 • Final chapter of my dissertation is out in Nature Human Behavior today! We described the journey from initial survey design all the way up to publication here. Thanks to my wonderful coauthors and the anonymous reviewers who helped to improve our paper!
APR / MAY 2022 • Gave a talk about our research on parenthood in academia at Santa Fe Institute, and finally got hooded. I also presented this work for Dani Basset’s lab group at UPenn. I’m on the program committee for IC2S2 and a reviewer for ICWSM.
SEPT 2021 • Was invited to give a talk about my dissertation work at the “Responsible Data Science and AI” speaker series at University of Illinois (virtually). Presented these two papers. Slides can be found here.
JUNE 2021 • Accepted an offer as a Data Scientist at Twitter. Our paper was selected as paper of the year by the International Society for Scientometrics and Informetrics (ISSI). Taking a little break from work
APR / MAY 2021 • I earned the Computer Science Department’s Outstanding Research Award! Gave a presentation about social class and epistemic inequalities in academia to faculty at University of Aberdeen (slides).
Socioeconomic Roots of Academic Faculty
Allison C. Morgan, Nick LaBerge, Daniel B. Larremore, Mirta Galesic, Jennie E. Brand, and Aaron Clauset. Nature Human Behavior, 6, 1625–1633, 2022.
The Unequal Impact of Parenthood in Academia
Allison C. Morgan, Samuel F. Way, Michael J. D. Hoefer, Daniel B. Larremore, Mirta Galesic, and Aaron Clauset. Science Advances, 7 (9) eabd1996, 2021.
Measuring the Predictability of Life Outcomes with a Scientific Mass Collaboration
Matthew J. Salganik, Ian Lundberg, Alexander T. Kindel [et al. including Allison C. Morgan]. PNAS, 117 (15) 2020.
Productivity, Prominence, and the Effects of Academic Environment
Samuel F. Way, Allison C. Morgan, Daniel B. Larremore, and Aaron Clauset. PNAS, 116 (17) 2019.
Prestige Drives Epistemic Inequality in the Diffusion of Scientific Ideas
Allison C. Morgan, Dimitrios Economou, Samuel F. Way, and Aaron Clauset. EPJ Data Science 7, 40, 2018.
Automatically Assembling a Full Census of an Academic Field
Allison C. Morgan, Samuel F. Way, and Aaron Clauset. PLOS ONE, 13 (8) e0202223, 2018.
The Misleading Narrative of the Canonical Faculty Productivity Trajectory
Samuel F. Way, Allison C. Morgan, Aaron Clauset, and Daniel B. Larremore. PNAS, 114 (44) E9216-E9223, 2017.