Haihao Lu

I am an assistant professor of Operations Management at the University of Chicago Booth School of Business. Before joining Chicago Booth, I was a faculty researcher at Google Research's large-scale optimization team. I obtained my Ph.D degree in Mathematics and Operations Research at MIT in 2019, working with Robert M. Freund.

My primary research focuses on 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. Currently, I am particularly enthused about two lines of research on first-order optimization algorithms:

i) Develop new first-order optimization algorithms and computational tools to scale up and speed up large-scale constrained continuous optimization problems by using GPUs and distributed computing. These optimization problems include but are not limited to linear programming, quadratic programming, second-order cone programming, and nonlinear programming.

ii) Develop new data-driven first-order optimization algorithms for the allocation of scarce resources. A motivation for this line of research is the budget pacing in online advertising platforms. I propose efficient and robust algorithms that can be applied to real-world applications and study their provable performance guarantees.

My research has been recognized by several research awards, including INFORMS Optimization Society Young Researchers Prize, INFORMS Michael H. Rothkopf Junior Research Paper Prize (first place), INFORMS Revenue Management and Pricing Section Prize. Notably, the algorithms and software developed in my research have been utilized in leading technology companies and generated significant revenue impacts. 

See my research page for a full list of publications.