Rate My Professor Alain Zemkoho

His research focuses on bilevel and hierarchical optimization, first- and second-order numerical methods for continuous optimization, nonsmooth and nonconvex optimization, stability/sensitivity analysis in optimization, and variational analysis with applications. These include transportation (toll setting, network design, demand estimation), data analysis, forecasting, trust topology, phase retrieval, machine learning problems with hierarchical structure, pricing, network design, and medicine. Key contributions include co-editing the book Bilevel Optimization: Advances and Next Challenges (Springer, 2020) and developing the BOLIB library of test problems for bilevel optimization (2020). He has authored numerous papers, such as "An inertial extrapolation method for convex simple bilevel optimization" (2021) and recent works on data-driven hull-fouling cleaning schedule optimization (2026) and multi-domain deception for automotive networks (2025).

Professor Zemkoho is an Alexander von Humboldt Experienced Fellow (2024-2026), a former Fellow of the Alan Turing Institute for Data Science and Artificial Intelligence (2019-2023), a Fellow of the Institute of Mathematics and Its Applications, and a Fellow of the Higher Education Academy. His publications have accumulated over 1,900 citations with an h-index of 21 (Google Scholar). He contributes to the field through appointment to the EPSRC Mathematical Sciences Strategic Advisory Team and invited lectures, including one on non-linear support vector machines in 2023.