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 I’m a PhD student in Public Policy and Biostatistics at UC Berkeley focusing on quantitative criminology. My qualifying paper Shedding Light on the Black Box: Machine Learning Applications to Criminal Justice Policy explores how statistical learning methods can be used to improve the life of individuals involved with the criminal justice system. I seek to combine machine learning tools and causal inference methods to understand and transform how society deals with crime. In my research, I value collaboration across disciplines and with practitioners and I am passionate about applying academic work to solve real world problems.


By Appointment

Statistical modeling, including regression analysis and causal inference in R and Python as well as machine learning, LaTeX, Git, and GitHub.