معرفی
Saeed Ghadimi is an Assistant Professor at the University of Waterloo, with affiliations in Data Analytics, Applied Operations Research, and Energy Market research groups. His work focuses on developing advanced optimization algorithms for stochastic systems, machine learning applications, and decision-making under uncertainty. He is particularly noted for contributions to bilevel programming, quantum optimal control, and robust regression techniques with missing data.
Research interests include optimization theory, stochastic programming, and interdisciplinary applications in energy systems and public policy. His methodologies often address nonconvexity, nonstationarity, and high-dimensionality challenges.
Recent work emphasizes projection-free algorithms, adversarial robustness in regression, and parametric cost function approximations for multistage problems. He maintains a personal webpage at https://sites.google.com/view/sghadimi.
