Sanyou Mei
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Education
Research Interests
Algorithm design and analysis for bilevel optimization, minimax optimization, stochastic optimization, distributed optimization, and online optimization
Applications for data science, AI/machine learning, healthcare, and decision-making under uncertainty
Honors
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.
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