Arkadi Nemirovski

John P. Hunter, Jr. Chair and
Professor

Contact

 Groseclose 446
 404.385.0769
 Personal website
 Curriculum Vitae
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  • Arkadi Nemirovski ResearcherID

Education

  • Ph.D. Mathematics (1974), Moscow State University
  • Doctor of Physical & Mathematical Sciences (1990), Supreme Attestation Board at the USSR Council of Ministers

Expertise

  • Convex and Continuous Optimization

About

Arkadi Nemirovski is the John P. Hunter, Jr. Chair in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Nemirovski's research interests focus on Optimization Theory and Algorithms, with emphasis on investigating complexity and developing efficient algorithms for nonlinear convex programs, optimization under uncertainty, applications of convex optimization in engineering, and nonparametric statistics.

Dr. Nemirovski has made fundamental contributions to continuous optimization in the last forty years that have significantly shaped the field. In recognition of his contributions to convex optimization, Nemirovski was awarded the 1982 Fulkerson Prize from the Mathematical Programming Society and the American Mathematical Society (joint with L. Khachiyan and D. Yudin), the 1991 Dantzig Prize from the Mathematical Programming Society and the Society for Industrial and Applied Mathematics (joint with M. Grotschel), the 2003 von Neumann Theory Prize of INFORMS (joint with M. Todd), the 2019 Norbert Wiener Prize in Applied Mathematics from AMS and SIAM (joint with M. Berger), the 2023 World Laureates Association Prize (joint with Yu. Nesterov), and the 2024 INFORMS Lanchester Prize (joint with A. Juditsky). He was elected to the National Academy of Engineering (2017), to the American Academy of Arts and Sciences (2018), and to the National Academy of Sciences (2020).

Dr. Nemirovski earned a Ph.D. in Mathematics (1974) from Moscow State University,  the Doctor of Sciences in Mathematics (1990) from the Supreme Attestation Board at the USSR Council of Ministers, and the Doctor of Mathematics (Honoris Causa) from the University of Waterloo, Canada (2009).

Research

My research interests are in the design and analysis of efficient convex optimization algorithms, with contributions to the Ellipsoid algorithm, polynomial time interior point methods for well-structured convex problems, and first-order methods, and in the  Convex Optimization theory (contributions to Conic Programming) and its applications in Engineering (structural design) and Statistics (Nonparameteric Statistics,  Signal Processing, and Hypothesis Testing).

Teaching

I am mostly teaching, in a traditional academic style as I understand it, graduate-level mathematically oriented courses on the descriptive, modeling, and algorithmic design components of Convex Optimization, and on applications of its machinery in Engineering and Statistics. I equip my courses with self-contained Lecture Notes available to my students via Canvas, and to the general public -- via my website.

Awards and Honors

  • The INFORMS Frederick W. Lanchester Prize (joint with A. Juditsky)
  • The World Laureates Association Prize in Mathematics or Computer Science (joint with Yu. Nesterov)
  • Elected to The National Academy of Sciences
  • Norbert Wiener Prize in Applied Mathematics from AMS and SIAM (with M. Berger)
  • Elected to  The American Academy of Arts and Sciences
  • Elected to The National Academy of Engineering 
  • Honoris Causa Degree of Doctor of Mathematics, University of Waterloo, Canada
  • John von Neumann Theory Prize of INFORMS (with M. Todd) 
  • Dantzig Prize of the Mathematical Programming Society and SIAM (with M. Grotschel) 
  • Fulkerson Prize of the Mathematical Programming Society and AMS (with L. Khachiyan and D. Yudin) 

Representative Publications

  • Nemirovsky, A., and Yudin, D. Problem complexity and method efficiency in optimization. - John Wiley & Sons, 1983.
  • Nesterov,   Yu.,   and  Nemirovskii,  A.  Interior point polynomial methods in Convex Programming. - SIAM
    Series in Applied Mathematics, SIAM: Philadelphia, 1994
  • Nemirovski, A. Topics in Non-parametric Statistics, in: M. Emery, A. Nemirovski, D. Voiculescu, Lectures on Probability Theory and Statistics, Ecole d'Ete\'e de Probabilit\'es de Saint-Flour XXVIII -- 1998, Ed. P. Bernard. - Lecture Notes in Mathematics v. 1738, Springer (2000), 87--285.
  • Ben-Tal, A., and Nemirovski, A.  Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering
       Applications. - MPS-SIAM Series on Optimization, SIAM, Philadelphia, 2001.
  • Ben-Tal, A., El Ghaoui, L., Nemirovski, A. Robust Optimization. -  Princeton University Press, 2009.
  • Juditsky, A., Nemirovski, A. Statistical Inference via Convex Optimization. - Princeton University Press, April 2020.
  1. Yudin,  D.,  and  Nemirovskii,  A.  "Information-based complexity and efficient methods of convex optimization." (in Russian) - Ekonomika i  Matematicheskie  Metody 12:2 (1976), 357-369.  English translation: Matekon
  2. Nemirovskii,   A.,   and   Yudin,   D.   On  Cezari's convergence of the steepest descent method for approximating
    saddle point of convex-concave functions.  - Soviet Math. Dokl. 19:2  (1978)
  3. A. Nemirovski. On forecast under uncertainty. Problemy Peredachi Informatsii 17:4 (1981), 73–83 (in Russian). English translation: Problems of  Information Transmission
  4. Nemirovskii,  A.,  and Nesterov,  Yu. Optimal methods for smooth convex optimization. (in Russian)  -  Jurnal
    Vychislitel'noi  Matematiki i Matematicheskoi Fiziki 25:2 (1985). English translation: USSR J. Comput. Math. & Math. Phys.
  5. Ibragimov,  I.,  Nemirovskii,  A., and Khasminskii, R. Some problems of nonparametric estimation under  Gaussian noise. (in  Russian)  -  Teoria veroyatnostei 31:3 (1986). English translation: Probability Theory and Math. Statist.
  6. Nemirovskii,  A.  On regularization by the  conjugate gradient  algorithm  as  applied  to ill-posed problems." (in
    Russian)  -   Jurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki 26:3 (1986). English translation: USSR J. Comput. Math. & Math. Phys.
  7. Nesterov,  Yu.,  and Nemirovskii,  A. Polynomial time barrier  methods  in  convex programming" (in Russian). - 
    Ekonomika i Matematicheskie Metody 24:6 (1988) . English translation: Matekon
  8. Nemirovskii, A. On optimality of Krylov's information when solving linear operator equations. -  Journal  of
    Complexity 7 (1991), 121-130
  9. Nesterov, Yu., and Nemirovskii, A. Conic duality and its applications in Convex Programming. - Optimization and
    Software 1 (1992), 95-115
  10. Lemarechal, C., Nemirovski, A., and Nesterov, Yu.New variants of bundle method. - Mathematical Programming 69:1 (1995), 111-148
  11. Goldenshluger, A. and Nemirovski, A.  Spatial adaptive estimation of functions satisfying differential inequalities. -IEEE Transactions on Information Theory 43 (1997), 872-889.
  12. Ben-Tal, A., and Nemirovski, A. Stable Truss Topology Design via Semidefinite Programming. - SIAM Journal on Optimization 7:4 (1997), 991-1016.
  13. Ben-Tal, A., and Nemirovski, A. Robust Convex Optimization. Mathematics of Operations Research 23:4 (1998)
  14. Ben-Tal, A., and Nemirovski, A. Robust solutions of Linear Programming problems contaminated with uncertain data. Mathematical Programming 88 (2000), 411-424.
  15. Ben-Tal, A., and Nemirovski, A. On polyhedral approximations of the second-order cone. - Mathematics of Operations Research 26:2 (2001)
  16. Nemirovski, A. Prox-method with rate of convergence (1/t) for variational inequalities with Lipschitz continuous monotone operators and smooth convex-concave saddle point problems. -  SIAM Journal on Optimization 15 (2004), 229--251.
  17. Ben-Tal, A., Boyd, S., Nemirovski, A. Extending the Scope of Robust Optimization: Comprehensive Robust Counterparts of Uncertain Problems. - Mathematical Programming Ser. B 107:1-2 (2006), 63--89.
  18. Nemirovski, A., Juditsky, A., Lan, G., Shapiro, A. Stochastic Approximation Approach to Stochastic Programming, -
    SIAM Journal on Optimization 9:4 (2009), 1574-1609.
  19. Juditsky, A., Nemirovski, A. Non-parametric estimation by Convex Programming. -  Annals of Statistics 37:5A}(2009), 2278-2300.
  20. Nemirovski, A., Onn, S., Rothblum, U. Accuracy certificates for computational problems with convex structure. -
    Mathematics of Operations Research 35:1 (2010), 52-78.
  21. Juditsky, A., Nemirovski, A. On sequential hypotheses testing via convex optimization. - Automation and Remote Control 76:5 (2015), 809-825
  22. Goldenshluger, A., Juditsky, A., Nemirovski, A.  Hypothesis testing by convex optimization. -Electron. J. Statist. 9:2 (2015), 1645--1712.
  23. Juditsky, A., Nemirovski, A. Solving Variational Inequalities with Monotone Operators on Domains Given by Linear Minimization Oracles.- Mathematical Programming 156:1-2 (2016), 221--256.
  24. Cox, B., Juditsky, A., Nemirovski, A. `Decomposition Techniques for Bilinear Saddle Point Problems and Variational Inequalities with Affine Monotone Operators. - Journal of Optimization Theory and Applications 172:2 (2017), 402-435.
  25. Juditsky, A., Nemirovski, A. Near-Optimality of Linear Recovery in Gaussian Observation Scheme under $\|\cdot\|_2^2$-Loss. -  Annals of Statistics 46:4 (2018), 1603-1629.
  26. Juditsky, A., Nemirovski, A.  On Polyhedral Estimation of Signals via Indirect Observations. - Electronic Journal of Statistics 14:1 (2020), 458-502.
  27. Kotsalis, G., Lan, G., Nemirovski, A. Convex optimization for finite-horizon robust covariance control of linear stochastic systems. - SIAM Journal on Control and Optimization 59:1 (2021), 296-319.
  28. Juditsky, A., Nemirovski, A.  On well-structured convex-concave saddle point problems and variational inequalities with monotone operators. -  Optimization Methods and Software 37:5 (2022), 1567-1602.
  29. Juditsky, A., Kotsalis, G., Nemirovski, A. Tight Computationally Efficient Approximation of Matrix Norms with Applications. -  Open Journal of Mathematical Optimization 3:7 (2022), 1-38.
  30. Bekri, Y., Juditsky, A., Nemirovski, A. Robust signal recovery under uncertain-but-bounded perturbations in observation matrix. -  Journal of Optimization Theory and Applications 205 paper # 55 - (2025)
  31. Bekri, Y., Juditsky, A., Nemirovski, A. Estimation from indirect observations under stochastic uncertainty in observation matrix. Journal of Optimization Theory and Applications 205 paper # 56 (2025)