Haihao (Sean) Lu

Assistant Professor
Chicago Booth

Haihao (Sean) Lu’s research interests are in extending the computational and mathematical boundaries of methods for solving the large-scale optimization problems that arise in data science, machine learning, and operations research. In particular, he is interested in (1) theory of convex and non-convex optimization motivated by statistical/machine learning problems; (2) data-driven decision making with applications in advertisement allocation and machine scheduling; and (3) huge-scale linear programming solving in the distributed setting (with applications at Google). His work has appeared in Mathematical Programming and SIAM Journal on Optimization.

Lu completed his PhD in operations research and applied mathematics at the Massachusetts Institute of Technology and his BS in applied mathematics at Shanghai Jiao Tong University. Previously, he was a visiting researcher at Google Research’s large-scale optimization team, where he primarily worked on designing and implementing a linear programming solver.

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Photo credit: Ruiting Liu