Sanyou Mei   梅三友

About Me

I am currently a fifth-year Ph.D. student in the Department of Industrial and Systems Engineering at University of Minnesota, where I am fortunate to be advised by Professor Zhaosong Lu. I finished my undergraduate study in the School of the Gifted Young at University of Science and Technology of China and obtained B.S. degree in Mathematics in 2020.

I will join the Department of Industrial Engineering and Decision Analytics at the Hong Kong University of Science and Technology as an Assistant Professor in this fall.

Education

• University of Minnesota
  Ph.D. in Industrial Engineering, Sept. 2020 -Present
  M.S. in Industrial and Systems Engineering, Sept. 2020 - Apr. 2023

• University of Science and Technology of China
  B.S. in Mathematics and Applied Mathematics, Sept. 2016 - Jun. 2020

Research Interests

• Algorithm design and analysis for bilevel, minimax, stochastic, distributed, and online optimization
• Applications for data science, AI/machine learning, healthcare, and decision-making under uncertainty

Honors

• INFORMS Optimization Society 2024 Student Paper Prize Honorable Mention
  for the paper "Accelerated first-order methods for convex optimization with locally Lipschitz continuous gradient" coauthored with Prof. Zhaosong Lu.
  

Research Papers

• Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees (with Z. Lu and Y. Xiao), submitted.
• A first-order method for nonconvex-strongly-concave constrained minimax optimization (with Z. Lu), submitted.
• Solving bilevel optimization via sequential minimax optimization (with Z. Lu), submitted.
• A first-order augmented Lagrangian method for constrained minimax optimization (with Z. Lu), accepted by Mathematical Programming, 2024.
• Primal-dual extrapolation methods for monotone inclusions under local Lipschitz continuity (with Z. Lu), to appear in Mathematics of Operations Research, 2024.
• First-order penalty methods for bilevel optimization (with Z. Lu), SIAM Journal on Optimization, 34(2), 1937-1969, 2024.
• Accelerated first-order methods for convex optimization with locally Lipschitz continuous gradient (with Z. Lu), SIAM Journal on Optimization, 33(3): 2275-2310, 2023.

Teaching

• IE 2021: Engineering Economics, Teaching Assistant, Fall 2021, 2022, 2023.
• IE 3011: Optimization I, Teaching Assistant, Fall 2021.
• IE 5531/MATH 5711: Engineering Optimization I, Teaching Assistant, Fall 2024.
• IE 5545: Decision Analysis, Teaching Assistant, Spring 2022.
• IE 5561: Analytics and Data-Driven Decision Making, Teaching Assistant, Spring 2022, 2023, 2024.
• IE 8564: Optimization for Machine Learning, Teaching Assistant, Fall 2022, 2024.