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. Active application areas include public health, orphanhood, and the big data paradox. I am working with colleagues from University of Oxford, Imperial College London, and University of Copenhagen to model the spread of COVID-19 and assess its impact on orphanhood. My research is currently supported by a £1.18 million EPSCRC Fellowship Award, “Spatiotemporal Statistical Machine Learning.”

Before my appointment at Oxford, I was a senior lecturer in statistical machine learning in the statistics section of the Department of Mathematics at Imperial College London, where I helped lead the Machine Learning Initiative at Imperial and the EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning (StatML) at Imperial and Oxford. I won a Samsung AI Researcher of the Year Award (2020) and began working with colleagues from the Department of Mathematics and School of Public Health to model the spread of COVID-19.

I completed my PhD at Carnegie Mellon University in August 2015 in a joint program between public policy and machine learning, supervised by Alex Smola and Daniel Neill. I spent a summer at Microsoft Research NYC in the computational social science group and visited the statistics department at Columbia University in my last year. I then undertook research as a postdoc with Yee Whye Teh at Oxford in the computational statistics and machine learning group in the Department of Statistics, when I helped make an animation answering the question, What is Machine Learning?

My undergraduate studies at Harvard were in mathematics and computer science, during which I took part in Harvey Mudd’s fantastic Research Experience for Undergraduates in summer 2006 and wrote an undergraduate thesis on connections between the Unique Games Conjecture and semidefinite programming-based approximation algorithms. After graduation, I lived in Switzerland, first studying at Ecole Polytechnique Fédérale de Lausanne (EPFL) and then working at the World Health Organization in the Mortality and Burden of Disease group in the Department of Health Statistics and Information on the Global Burden of Disease project and the Nutrition Impact Model Study. I have continued to collaborate on research with Global Burden of Disease and WHO colleagues.

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