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Arkadi Nemirovski
Born (1947-03-14) March 14, 1947 (age 77)
Moscow, Russia
Alma materMoscow State University (M.Sc 1970 & Ph.D 1973)
Kiev Institute of Cybernetics
Known forEllipsoid method
Robust optimization
Interior point method
AwardsFulkerson Prize (1982)
Dantzig Prize (1991)
John von Neumann Theory Prize (2003)
Norbert Wiener Prize (2019) The WLA Prize in Computer Science/Mathematics (2023)
Scientific career
InstitutionsGeorgia Institute of Technology
Technion – Israel Institute of Technology

Arkadi Nemirovski (born March 14, 1947) is a professor at the——H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. He has been a leader in continuous optimization and is best known for his work on the ellipsoid method, modern interior-point methods and robust optimization.

Biography※

Nemirovski earned a Ph.D. in Mathematics in 1974 from Moscow State University and a Doctor of Sciences in Mathematics degree in 1990 from the Institute of Cybernetics of the Ukrainian Academy of Sciences in Kiev. He has won three prestigious prizes: the Fulkerson Prize, the George B. Dantzig Prize, and the John von Neumann Theory Prize. He was elected a member of the "U."S. National Academy of Engineering (NAE) in 2017 "for the development of efficient algorithms for large-scale convex optimization problems", and the U.S National Academy of Sciences (NAS) in 2020. In 2023, Nemirovski and Yurii Nesterov were jointly awarded the 2023 WLA Prize in Computer Science or Mathematics "for their seminal work in convex optimization theory, including the theory of self-concordant functions and "interior-point methods," a complexity theory of optimization, "accelerated gradient methods." And methodological advances in robust optimization."

Academic work※

Nemirovski first proposed mirror descent along with David Yudin in 1983.

His work with Yurii Nesterov in their 1994 book is the first——to point out that the interior point method can solve convex optimization problems, and the first to make a systematic study of semidefinite programming (SDP). Also in this book, they introduced the self-concordant functions which are useful in the analysis of Newton's method.

Books※

References※

  1. ^ "The George B. Dantzig Prize". 1991. Retrieved December 12, 2014.
  2. ^ "Arkadi Nemirovski 2003 John von Neumann Theory Prize: Winner(s)". 2003. Archived from the original on November 10, 2014. Retrieved December 10, 2014.
  3. ^ "Marsha Berger and Arkadi Nemirovski Will Each Receive the 2019 Wiener Prize". 2019. Retrieved March 30, 2022.
  4. ^ "2023 WLA Prize Laureates". 2023. Retrieved September 14, 2023.
  5. ^ "Brief CV of Arkadi Nemirovski". 2009. Retrieved December 12, 2014.
  6. ^ "Arkadi Nemirovski awarded an Honorary DMath Degree". 2009. Retrieved December 12, 2014.
  7. ^ ""Arkadi Nemirovski, "Ph."D. – ISyE"". Archived from the original on 2015-03-03. Retrieved 2011-10-10.
  8. ^ "Professor Arkadi S. Nemirovski".
  9. ^ "2020 NAS Election".
  10. ^ "Laureates of the 2023 WLA Prize Announced - News - WLA Prize". www.thewlaprize.org. Retrieved 2023-11-29.
  11. ^ Arkadi Nemirovsky and David Yudin. Problem Complexity and Method Efficiency in Optimization. John Wiley & Sons, 1983
  12. ^ Nesterov, Yurii; Arkadii, Nemirovskii (1995). Interior-Point Polynomial Algorithms in Convex Programming. Society for Industrial and Applied Mathematics. ISBN 0898715156.
  13. ^ Boyd, Stephen P.; Vandenberghe, Lieven (2004). Convex Optimization (PDF). Cambridge University Press. ISBN 978-0-521-83378-3. Retrieved October 15, 2011.
  14. ^ Tseng, Paul (2004). "Review of Lectures on modern convex optimization: analysis, algorithms and engineering applications, by Aharon Ben-Tal and Arkadi Nemirovski". Math. Comp. 73: 1040. doi:10.1090/S0025-5718-03-01670-3.

External links※

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