World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
57
Citations
18784
World Ranking
672
National Ranking
339

Engineering and Technology

D-Index
57
Citations
18811
World Ranking
2584
National Ranking
784

Research.com Recognitions

  • 2018 - Dantzig Prize, by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS)
  • 2017 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)

Overview

Andrzej Ruszczyński is affiliated with Rutgers, The State University of New Jersey in the United States. Their research spans areas within mathematics and decision sciences, focusing particularly on statistics and probability, management science and operations research, and artificial intelligence.

The scientist's work covers a number of specialized topics, including:

  • Risk and Portfolio Optimization
  • Sparse and Compressive Sensing Techniques
  • Statistical Methods and Inference
  • Stochastic Gradient Optimization Techniques
  • Stochastic processes and financial applications
  • Markov Chains and Monte Carlo Methods
  • Fuzzy Systems and Optimization

Among their recent papers are the following:

  • "A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization," 2020, published in SIAM Journal on Optimization
  • "A Stochastic Subgradient Method for Nonsmooth Nonconvex Multilevel Composition Optimization," 2021, published in SIAM Journal on Control and Optimization
  • "A Stochastic Subgradient Method for Distributionally Robust Non-convex and Non-smooth Learning," 2022, published in Journal of Optimization Theory and Applications
  • "A Dual Method For Evaluation of Dynamic Risk in Diffusion Processes," 2020, published in ESAIM Control Optimisation and Calculus of Variations
  • "Risk filtering and risk-averse control of Markovian systems subject to model uncertainty," 2023, published in Mathematical Methods of Operations Research

Frequent co-authors in their research include Darinka Dentcheva, Alexander Shapiro, Mert Gürbüzbalaban, Landi Zhu, and Shangzhe Yang.

Their publications have appeared regularly in venues such as:

  • arXiv (Cornell University)
  • SIAM Journal on Optimization
  • SIAM Journal on Control and Optimization
  • Mathematical Programming
  • Annals of Operations Research

Andrzej Ruszczyński has contributed to book publications with the Society for Industrial and Applied Mathematics and Springer International Publishing. Notable titles include:

  • Lectures on Stochastic Programming: Modeling and Theory, Third Edition, 2021 (Society for Industrial and Applied Mathematics)
  • Risk-Averse Optimization and Control, 2024 (Springer International Publishing)

Awards received include the Dantzig Prize from the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS) in 2018, and fellowship in the Institute for Operations Research and the Management Sciences (INFORMS) since 2017.

Best Publications

  • Lectures on Stochastic Programming: Modeling and Theory

    Alexander Shapiro;Darinka Dentcheva;Andrzej P. Ruszczyński

  • Nonlinear optimization

    Andrzej Ruszczynski

  • From stochastic dominance to mean-risk models: Semideviations as risk measures

    Włodzimierz Ogryczak;Andrzej Ruszczyński

  • A branch and bound method for stochastic global optimization

    Vladimir I. Norkin;Georg Ch. Pflug;Andrzej Ruszczyński

  • Dual stochastic dominance and related mean-risk models

    Włodzimierz Ogryczak;Andrzej Ruszczyński

  • Optimization of Convex Risk Functions

    Andrzej Ruszczyński;Alexander Shapiro

  • A New Scenario Decomposition Method for Large-Scale Stochastic Optimization

    John M. Mulvey;Andrzej Ruszczyński

  • Stochastic Programming Models

    Andrzej Ruszczyński;Alexander Shapiro

  • Risk-averse dynamic programming for Markov decision processes

    Andrzej Ruszczyński

  • Optimization with Stochastic Dominance Constraints

    Darinka Dentcheva;Andrzej Ruszczynski

  • Lectures on Stochastic Programming: Modeling and Theory, Second Edition

    Alexander Shapiro;Darinka Dentcheva;Andrzej Ruszczynski

  • A regularized decomposition method for minimizing a sum of polyhedral functions

    A Ruszczyński

  • On consistency of stochastic dominance and mean–semideviation models

    Włodzimierz Ogryczak;Andrzej Ruszczyński

  • Conditional Risk Mappings

    Andrzej Ruszczyński;Alexander Shapiro

  • Concavity and Efficient Points of Discrete Distributions in Probabilistic Programming

    Darinka Dentcheva;András Prékopa;Andrzej Ruszczynski

  • Portfolio optimization with stochastic dominance constraints

    Darinka Dentcheva;Andrzej Ruszczyński

  • Decomposition methods in stochastic programming

    Andrzej Ruszczyński

  • Lectures on Stochastic Programming: Modeling and Theory, Third Edition

    Unknown

  • ON THE INTEGRATED PRODUCTION, INVENTORY AND DISTRIBUTION ROUTING PROBLEM

    Lei Lei;Shuguang Liu;Andrzej Ruszczynski;Sunju Park

  • Parallel decomposition of multistage stochastic programming problems

    Andrzej Ruszczyński

  • Probabilistic programming with discrete distributions and precedence constrained knapsack polyhedra

    Andrzej Ruszczyński

  • SIAM Journal on Optimization

    C Audet;H H Bauschke;L T Biegler;P L Combettes

Frequent Co-Authors

Alexander Shapiro
Alexander Shapiro Georgia Institute of Technology
Włodzimierz Ogryczak
Włodzimierz Ogryczak Warsaw University of Technology
András Prékopa
András Prékopa Rutgers, The State University of New Jersey
Rüdiger Schultz
Rüdiger Schultz University of Duisburg-Essen
Luís Nunes Vicente
Luís Nunes Vicente Lehigh University
Michael C. Ferris
Michael C. Ferris University of Wisconsin–Madison
Philippe L. Toint
Philippe L. Toint University of Namur
Masao Fukushima
Masao Fukushima Kyoto University
Jacek Gondzio
Jacek Gondzio University of Edinburgh
Markus Amann
Markus Amann International Institute for Applied Systems Analysis

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students pursuing Mathematics in the USA, exploring related online degrees can open diverse career opportunities. For instance, a masters in digital marketing can complement analytical skills with strategic marketing expertise, making graduates valuable in data-driven marketing roles.

Many professionals also consider accelerated programs like year long mba programs to fast-track leadership roles in business, finance, or technology sectors. These intensive courses help sharpen business acumen while leveraging a strong mathematical foundation.

Flexibility is key, which is why options such as an online mba with transfer credits accepted offer the convenience of continuing education without disrupting current work or study commitments.

Additionally, as data continues to drive decision-making globally, pursuing an ms in data analytics provides advanced skills in data interpretation and predictive modeling, positioning graduates for lucrative roles in tech, healthcare, finance, and more.

Best Scientists Citing Andrzej Ruszczyński

Trending Scientists

Recently Published Articles