As a professor in the computer science and engineering department at the University of California, San Diego, my main research interests are in machine learning and data science. I work especially on foundational questions raised by applications in business and biomedicine. Research in my group has been funded by an R01 grant from the National Institutes of Health, by a grant from the University of California National Lab cooperation program, and by gifts from Intel and other companies. My doctorate is in computer science from Cornell University, with a graduate minor in economics. As a graduate student I also spent time at Stanford University, and before joining UCSD I was a postdoctoral fellow at the University of Toronto. My undergraduate degree is in mathematics from Cambridge University, with a focus on statistics and optimization. In 1998/99 I was a visiting associate professor at Harvard University. Since the spring of 2014 I have been on leave from UCSD, working as Amazon Fellow and as leader of Amazon's central machine learning team in Seattle and Palo Alto. In winter 2014, I taught CSE 250B, a graduate course on machine learning. In spring 2013 I taught CSE 255, a graduate course on data science and analytics, while in fall 2012 I taught CSE 250A, a different graduate course on machine learning.