Yury is a graduate of the Moscow Institute of Physics and Technology (MIPT). After obtaining the Candidate of Sciences degree in discrete mathematics, he joined INRIA Rhone –Alpes and Grenoble Alpes University, France, as a postdoctoral researcher and turned his interest to statistical machine learning and optimization. Today, his research interests and experience include discrete mathematics, huge-scale convex optimization, statistics and statistical machine learning, as well as their engineering. Throughout his career, Yury always showed a deep appreciation of fundamental knowledge and strong practical motivation. He was a Team Lead and PI of multiple industrial projects on huge-scale optimization for telecommunication and railways networks. Prior to joining Skoltech, Yuri was an Associate Professor at the Department of Computer Science at the National Research University Higher School of Economics (HSE), MIPT Department of Control and Applied Mathematics, and a Research scientist at the Institute for Information Transmission Problem RAS (IITP RAS).
In 2015, Yury formed a research group “Optimization and Statistical Learning” of talented BSc, MSc and PhD students from MIPT, HSE and IITP, who conduct the research on the border of numerical optimization, computational complexity and statistics/statistical learning with a special focus on application of the research results in networking, engineering and physics. They also do research motivated by industrial applications arising from their collaboration within IITP and PreMoLab MIPT teams with Huawei, Genplan Moscow and other companies.
Yury is also an inspiring teacher readily sharing his knowledge and encouraging his students to take upon real challenges. Yuri taught undergraduate and graduate courses in applied mathematics at MIPT and HSE, and gave a number of invited talks and lectures at Weierstrass Institute for Applied Analysis and Stochastics (Berlin), Yandex (Yekaterinburg), Baltic Federal University (Kaliningrad), Bosch (Stuttgart) among others. Since November of 2015, Yury has held weekly research seminars on Modern Huge-Scale Optimization at IITP RAS.
Optimization, learning and engineering applications: discrete and convex optimization, computational complexity, statistical learning, network design and control (including engineering problems that arise in power flow and transportation networks).
REFEREED JOURNAL PUBLICATIONS:
14. Maximov Yu. and M. Mendel. “Efficient Traffic Measurements for Huge-Scale Internet Networks via Convex Optimization” European Chapter on Combinatorial Optimization (ECCO-29), Budapest, May 2016.
21. Maximov, Yu. “Improved polynomial time approximation guarantees for well structured quadratic optimization problem”, The 5th International Conference on Network Analysis (NET-2015), Nizhny Novgorod, May 2015.
23. Maximov, Yu. Effective numerical methods for huge-scale sparse linear systems with applications to the PageRank problem. University Grenoble-Alpes, Grenoble, France. 27 July, 2016 (anticipated).
ФИО: Максимов Юрий Владимирович
Занимаемая должность (должности): Старший Преподаватель
Ученая степень: Кандидат физико-математических наук по специальности “Дискретная математика”, 2012, Московский физико-технический институт
Ученое звание (при наличии): нет
Наименование направления подготовки и/или специальности: Прикладные физика и математика
Данные о повышении квалификации и/или профессиональной переподготовке (при наличии): нет
Общий стаж работы: 7 лет
Стаж работы по специальности: 7 лет