Arkadi Nemirovski
Born (1947-03-14) March 14, 1947
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)[1]
John von Neumann Theory Prize (2003)[2]
Norbert Wiener Prize (2019)[3] The WLA Prize in Computer Science or Mathematics (2023)[4]
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.[5] 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.[6]

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.[7] 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",[8] and the U.S National Academy of Sciences (NAS) in 2020.[9] 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."[10]

Academic work

Nemirovski first proposed mirror descent along with David Yudin in 1983.[11]

His work with Yurii Nesterov in their 1994 book[12] 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.[13]

Books

  • co-authored with Yurii Nesterov: Interior-Point Polynomial Algorithms in Convex Programming. Society for Industrial and Applied Mathematics. 1994. ISBN 978-0898715156.
  • co-authored with Aharon Ben-Tal: Lectures on Modern Convex Optimization. Society for Industrial and Applied Mathematics. 2001. ISBN 978-0-89871-491-3.[14]
  • co-authored with A. Ben-Tal and L. El Ghaoui: Robust Optimization. Princeton University Press. 2009. ISBN 978-0-691-14368-2.

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.
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