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Dr. Georg Pflug

Full Professor

Department of Statistics and Operations Research
Faculty of Business, Economics and Statistics
University of Vienna
Oskar-Morgenstern-Platz 1
1090 Wien, Austria

mail: georg.pflug [@] univie.ac.at
phone: +43 1 4277 38630


Research area in the programme
Stochastic Optimization



  • Stochastic optimization
  • Scenario generation algorithms
  • Decomposition algorithms
  • Bilevel stochastic problems
  • Stochastic equilibria models


Research interest

Approximation of large scale problems, distance concepts for stochastic models, Avoiding random sampling in dynamic algorithms, necessary optimality conditions for stochastic bilevel problems, stochastic MPEC problems.


Know-how and infrastructure of the research group

Georg Pflug works in the area of stochastic optimization. His interests cover the full scope from statistical data analysis and scenario process generation over approximation and bounding methods to algorithmic issues such as decomposition methods and dynamic optimization formulations of stochastic programs.   

A special emphasis of his research program lies on multistage stochastic programs. After having published a book on risk functionals with lots of material on multistage risk functionals (Pflug, Römisch, Modeling, Measuring and Managing Risk, World Scientific 2007) he wrote a new book on multistage stochastic programming with coauthor Alois Pichler (Springer, 2014).

An important  result deals with approximation of stochastic programs  w.r.t. the nested distance, a generalization of the Wasserstein distance (Pflug and Pichler, 2012).  This result has various consequences on scenario generation, bounding techniques and algorithmic issues.

As to the algorithmic side, Georg Pflug has designed new decomposition algorithms for risk-sensitive multistage stochastic programs (published in 2014). He is also an author and editor of a new book on Risk Management in Energy Production and Trading (Springer), an application area of optimization, which is also quite relevant for training the PhD candidates. 

The group of Prof. Pflug at the Department of Statistics and Operations Research at the University of Vienna consists of 6 scientific collaborators. Prof. Walter Gutjahr is also associated to this group. The necessary infrastructure (rooms, computing facilities, staff, etc.)  is available to conduct these projects.


Scientific CV


Study of Law, Mathematics and Statistics at the University of Vienna, Magister iuris (1974), Ph.D in Mathematics (1976). Assistant Professor University of Vienna (1976-81). Professor, University of Giessen, Germany (1981-1989). Full Professor, University of Vienna (1989 - now), Head of the Computational Risk Management Group at the University of Vienna. 

Visting Professor at the University of Bayreuth (1979), Michigan State University (1985), University of California Davis (1993), Université de Rennes (1994), Technion Haifa, Israel (1996), Princeton University (2001), University of California Davis (2006).

Editor-in-Chief: Statistics and Risk Modeling.

Associate Editor: Statistics and Probability Letters (-2007);  Stochastic Programming Electronic Publication Series; Central European Journal of Operations Research; Austrian Journal of Statistics, Mathematics of Operations Research (1994 - 1997); Mathematical Methods of OR; Computational Optimization and Applications; Computational Management Science; Energy Systems: Optimization, Modeling, Simulation and Economic Aspects; Journal of Stochastic Analysis, Financial Mathematics and Applications.

Author of 5 books, editor of 8 books, and more than 90 publications in refereed journals, such as: Annals of Statistics, Annals of OR, Probability Theory, J Statist. Planning and Inference, J. ACM, Parallel Computing, The Computer Journal, Math. Programming, Mathematics of Optimization, SIAM J. on Optimization, Computational Optimization and Applications, J. Applied Probability, Stoch. Processes and Applications, Graphs and Combinatorics, J. Theoretical Computer Science, Journal of Banking and Finance, Quantitative Finance, Risk Analysis, Finance and Stochastics etc.


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