Petrovsky Alexey B. is Professor, Doctor of Technical Sciences on System Analysis and Automated Control, Head of Department for Decision Problem, Chief Researcher, Federal Research Center “Computer Sciences and Control”, the Russian Academy of Sciences, Moscow, Russia, and Invited Professor at Moscow Physics and Technical Institute—National Research University (2004–2015), N.E. Bauman Moscow State Technical University (2006–2015), M.V. Lomonosov Moscow State University (2007–2010), Belgorod State National Research University (2010–2019), V.G. Shukhov Belgorod State Technological University (2011–2022), Volgograd State Technical University (2017-2022), Russia and graduated from M.V. Lomonosov Moscow State University (1967) and has Ph.D. degree on Theoretical and Mathematical Physics from V.A. Steklov Mathematical Institute and the USSR Academy of Sciences (1970).
Petrovsky Alexey B. is Editor-in-Chief and Member of Editorial Council, “Artificial Intelligence and Decision Making”, a journal of the Russian Academy of Sciences; Member of Editorial Boards: International Journal of Decision Support Systems, International Journal “Information Models and Analysis”, International Journal “Information Technologies and Knowledge”, “Proceedings of the Institute for Systems Analysis of the Russian Academy of Sciences”, “Strategic Decisions and Risk-Management”; a member of Editorial Council, and “Automation of Control Processes”.
Petrovsky Alexey B. is Member of the International Society on Multiple Criteria Decision Making, the European Working Group “Multiple Criteria Decision Aiding”; the Commission for working with young researchers of the Russian Academy of Sciences, the Russian Association for Artificial Intelligence; Full Member of the Russian Academy of Natural Sciences.
Petrovsky Alexey B. is Author of over 200 papers, including 7 monographs and 2 textbooks.
Research areas include discrete mathematics, multiset theory, multicriteria decision making, verbal decision analysis, decision support systems, information technologies, systems analysis, science and technology policy, R&D forecasting, and planning and management.