I am a fifth-year Ph.D. candidate in Operations Research at MIT advised by Juan Pablo Vielma. I received my B.S. in Applied Mathematics and M.S. in Statistics from the University of Chicago in 2011. After graduating, I spent a year as a researcher at Argonne National Laboratory before starting at MIT. I am excited to be joining Google Research in New York City in September 2017!
My research interests span diverse areas of mathematical optimization, with a unifying theme of developing new methodologies for large-scale optimization drawing from motivating applications in renewable energy. I have published work in chance constrained optimization, mixed-integer conic optimization, robust optimization, stochastic programming, algebraic modeling, automatic differentiation, numerical linear algebra, and parallel computing techniques for large-scale problems.
In 2012, Iain Dunning and I (later joined by Joey Huchette) started developing JuMP, an open-source algebraic modeling language for optimization. Since then, JuMP has been used for teaching in at least 10 universities and by numerous researchers and companies worldwide. We were recently awarded the INFORMS Computing Society prize for this work. I'm always interested to hear of who's using JuMP, so please get in touch.
In addition to the above academic talks, I have given JuMP tutorials, often together with fellow developers, at University of British Columbia (November 2016), Imperial College London (September 2016), Universidade Federal do Paraná (July 2016, in mostly Portuguese), Optimization Days 2016 (May 2016), JuliaCon 2015 (June 2015), MIT Energy Initiative (April 2015), Carnegie Mellon University (March 2015), Grid Science Winter School (January 2015), UC Berkeley (November 2014), Universidad Adolfo Ibañez (January 2014, in Spanish), and MIT Operations Research Center (October 2013).