Hi! I’m Abby and I live in San Francisco. I’m broadly interested in making tools from statistics and machine learning more transparent, useful, and ethical, especially when deployed in domains with high social impact. I’m currently a research scientist in the Social and Behavioral Systems group at Argonne National Laboratory, where I develop statistical methods that make large-scale experimentation with complex mechanistic simulators, like climate and epidemiological models, more computationally feasible and accessible to decision-makers.

I got a PhD in Statistics from UChicago in 2022, where I was advised by Becca Willett and studied interpretability in machine learning methods. Before that, I worked for a few years as a data scientist at Doximity. I graduated with a math degree from Grinnell College in 2014.

I had a great time organizing Women in Data Science Chicago during grad school, and have been involved in a number of data science for social good initiatives such as the Data Science Working Group at Code for San Francisco and the Center for Data Science and Public Policy.

I’m also very passionate about things like food and wine and traveling and hiking and reading and listening to music and hanging out, and I always have a new craft on rotation (silver clay, as of the latest update).