He received his Ph.D. degree in operations research from Columbia University in 2011. His research focuses on developing first-order algorithms for large-scale convex optimization problems from diverse application areas, such as distributed optimization, robust matrix decomposition, convex regression, and compressed sensing. His current research is supported by two NSF grants: one on designing optimization algorithms that simultaneously learn missing model parameters of a given parametric model, and the other one on designing smart power grids through distributed optimization.