Paul's research interests include large-scale convex optimization, statistical machine learning, and data-driven decision making. He is also interested in applications in online advertising and data analytics, among other areas. Paul was recently awarded the 2015 INFORMS Optimization Society Student Paper Prize, and he was the recipient of an NSF Graduate Research Fellowship. Paul received his PhD in Operations Research from MIT in 2016. Previously, he earned a B.S. in Operations Research and Information Engineering from Cornell University.
- Large-scale convex optimization
- Statistical machine learning
- Data-driven decision-making
- ``An Extended Frank-Wolfe Method with `In-Face' Directions, and its Application to Low-Rank Matrix Completion," with Robert M. Freund and Rahul Mazumder, to appear in SIAM Journal on Optimization.
- ``A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives," with Robert M. Freund and Rahul Mazumder, to appear in Annals of Statistics.
- ``New Analysis and Results for the Frank-Wolfe Method," with Robert M. Freund, Mathematical Programming 155 (1), pp. 199-230, 2016.