about

I am a second year PhD student in Computer Science at Princeton University advised by Lydia Liu. I am interested in algorithmic fairness and the ethics and politics of algorithmic decision-making, and in particular using methodology from causal inference to study these topics. In addition, I have interests in the overlap of these topics with philosophy.

I graduated with a BA in Computer Science and English from Columbia University in 2019, an MPhil in Philosophy from Trinity College Dublin in 2020, supported by a George J. Mitchell Scholarship, and, supported by a Knight-Hennessy Scholarship, an MS in Symbolic Systems at Stanford University in 2024, where I was advised by Thomas Icard.

More About My Research Interests

I am broadly interested in the ways that algorithmic decision-making might impact outcomes and fairness of decision making in complex bureaucracies, viewing the provision of algorithmic decision support as a social intervention. (This white paper has been very influential on me). The first project of my PhD looked at the role of advisor discretion in targeting interventions in an algorithm-assisted college advising program.

I love finding ways to intersect my technical interests with ideas from philosophy. Lately I have been thinking about group/multi-calibration from the perspective of accuracy-first epistemology and how to perform causal manipulations on socially-constructed variables, e.g. to test for discrimination.

The COVID Tracking Project

From 2020 to 2021, I co-led (with the amazing Michal Mart) the data quality team of The COVID Tracking Project at The Atlantic. We oversaw daily decision-making about a testing & disease outcomes dataset that received millions of API requests, was used by the federal government, and displayed on dashboards including the New York Times and Johns Hopkins Coronavirus dashboards. 

The project, more broadly, was a 300 person mostly volunteer organization that emerged out of thin air to compile state-level US COVID-19 data for the first year of the pandemic. Participation in that project demonstrated to me the immense power of building intentional communities rooted in care -- manifested in CTP's case as careful work, care for those who relied on the data, and as care for each other. You can read more about what made the project tick, from its co-founder Erin Kissane, here.