Stonyakin Fedor Sergeyevich
Doctor of Physical and Mathematical Sciences, Leading Researcher at the Laboratory of Advanced Combinatorics and Network Applications, Professor at the Department of Discrete Mathematics of FPMI at MIPT (instructor of the courses “Optimization Methods,” “Optimization Methods in Machine Learning,” and “Selected Topics in Nonsmooth and Nonconvex Optimization”), and Head of the Department of Algebra and Functional Analysis at the V.I. Vernadsky Crimean Federal University.
Author of more than 80 scientific works, including 56 publications indexed in the international databases Scopus and WoS, and 6 papers in Q1 Scopus journals.
His research interests include: optimization methods in high- and ultra-high-dimensional spaces, analysis of adaptive and universal numerical optimization methods, methods for variational inequalities and saddle-point problems, convex and nonsmooth analysis, and optimization with inexact information.
Winner of competitions for Presidential Grants of the Russian Federation for young scientists (Candidates of Science), as well as project leader for grants from the Russian Science Foundation (RSF) and the Russian Foundation for Basic Research (RFBR) in the field of optimization for young researchers.
https://www.mathnet.ru/links/51fe01a38fdb626f60866dfe752f8a91/kvant1481.pdf
Doctor of Physical and Mathematical Sciences, Leading Researcher at the Laboratory of Advanced Combinatorics and Network Applications, Professor at the Department of Discrete Mathematics of FPMI at MIPT (instructor of the courses “Optimization Methods,” “Optimization Methods in Machine Learning,” and “Selected Topics in Nonsmooth and Nonconvex Optimization”), and Head of the Department of Algebra and Functional Analysis at the V.I. Vernadsky Crimean Federal University.
Author of more than 80 scientific works, including 56 publications indexed in the international databases Scopus and WoS, and 6 papers in Q1 Scopus journals.
His research interests include: optimization methods in high- and ultra-high-dimensional spaces, analysis of adaptive and universal numerical optimization methods, methods for variational inequalities and saddle-point problems, convex and nonsmooth analysis, and optimization with inexact information.
Winner of competitions for Presidential Grants of the Russian Federation for young scientists (Candidates of Science), as well as project leader for grants from the Russian Science Foundation (RSF) and the Russian Foundation for Basic Research (RFBR) in the field of optimization for young researchers.
https://www.mathnet.ru/links/51fe01a38fdb626f60866dfe752f8a91/kvant1481.pdf
