I study conceptual and empirical questions in social applications of AI/ML systems. My dissertation focuses on the social biases and human-algorithm interactions of predictive algorithms used in the criminal legal system, including risk assessment algorithms and predictive policing. I integrate approaches in philosophy of science and AI ethics, qualitative research methods in sociology of technology and law, and quantitative approaches in computer science to measure and understand the sources of algorithmic bias.

I hold a BS in Computer Science and have a research background in applied data science. Part of my PhD was funded through an NSF graduate research fellowship. I have also worked with research groups at the University of Colorado Boulder, University of Utah, and Harvard Medical School.