I am a PhD student of 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. Before coming to graduate school I work on policy implementation for a few years.
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I am PhD student of 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. Before coming to graduate school I work on policy implementation for a few years.
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Trainings
February 27, 2020
February 25, 2020
September 27, 2019
Consulting
statistical modeling, causal inference, regression analysis, Machine learning
Not currently available.
statistical modeling, causal inference, regression analysis, Machine learning
Not currently available.
statistical modeling, causal inference, regression analysis, Machine learning
Not currently available.
Statistical modeling, including regression analysis and causal inference in R and Python as well as machine learning, LaTeX, Git, and GitHub.
