I am an associate professor at the University of Oxford in the Department of Computer Science and a tutorial fellow of Jesus College. My research is on scalable methods and flexible models for spatiotemporal statistics and Bayesian machine learning, applied to public policy and social science. I’ve worked on application areas that include public health, orphanhood, deep learning from satellite and street-level imagery, crime, voting patterns, filter bubbles / echo chambers in media, the big data paradox, the regulation of machine learning algorithms, and emotion.
I am working with colleagues from University of Oxford, Imperial College London, and University of Copenhagen to model the spread of COVID-19.
PhD in Machine Learning and Public Policy, 2015
Carnegie Mellon University
BA Mathematics and Computer Science, 2008