Haihao Lu

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Haihao Lu

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Haihao Lu is the Cecil and Ida Green Career Development Assistant Professor, and an Assistant Professor of Operations Research/Statistics at the MIT Sloan School of Management. Before joining MIT Sloan, he was an Assistant Professor at the University of Chicago Booth School of Business and a faculty researcher at Google Research's large-scale optimization team. He obtained his PhD degree in Mathematics and Operations Research at MIT in 2019.

Lu’s research lies at the intersection of optimization, computation, and data science, with a focus on pushing the computational and mathematical frontiers of large-scale optimization. Much of his work is inspired by real-world challenges faced by leading technology companies and optimization software companies. Currently, he is particularly excited about two lines of research:

First-order methods and scalable solvers: Lu develops new first-order optimization algorithms, theoretical guarantees, and computational tools to accelerate and scale mathematical programming using modern computing architectures such as GPUs and distributed systems. These tools address a range of problems, including linear programming, quadratic programming, semidefinite programming, and nonlinear programming. Notably, the PDLP algorithm he codeveloped has been widely adopted by industry-leading solvers and tech companies, including Google, NVIDIA, Gurobi, COPT, HiGHS, Knitro, and FICO Xpress.

Data-driven optimization for resource allocation: Lu also designs new algorithms with provable performance guarantees for allocating scarce resources in uncertain environments. A key application area is budget pacing in online advertising, where his algorithms have been deployed by major platforms such as Google and eBay to improve efficiency and robustness.

His research has been recognized by several research awards, including COIN-OR Cup, the Beale—Orachard-Hays Prize, the INFORMS Optimization Society Young Researchers Prize, the INFORMS Michael H. Rothkopf Junior Research Paper Prize (first place), and the INFORMS Revenue Management and Pricing Section Prize. The algorithms and software developed through his research have had real-world impact, generating substantial revenue and advancing the state of practice in large-scale optimization.

Honors

Lu wins 2024 COIN-OR Cup

December 16, 2024

Mathematical Optimization Society honors Lu

July 31, 2024

Lu wins INFORMS prize

October 15, 2023

Lu wins Rothkopf prize

October 16, 2022

INFORMS awards Young Researcher Prize to Lu

October 24, 2021

Publications

"A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming."

Lu, Haihao and Jinwen Yang. Mathematical Programming. Forthcoming.

"cuPDLP. jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia."

Lu, Haihao and Jinwen Yang. Operations Research. Forthcoming. arXiv Preprint.

"Optimizing Scalable Targeted Marketing Policies with Constraints."

Lu, Haihao, Duncan Simester, and Yuting Zhu. Marketing Science. Forthcoming. SSRN.

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