My research lies broadly in mathematical optimization, at its interface with statistics, learning, and networks, with an emphasis on scalable algorithms for large-scale problems and their guarantees.
Current interests include distributed optimization and learning over networks, high-dimensional statistical inference, adaptive (parameter-free) methods, and decomposition principles for graph-structured programs and equilibrium problems (variational inequalities and games).