World's Best Scientists 2026 revealed!

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Mathematics

D-Index
45
Citations
9654
World Ranking
1457
National Ranking
26

Engineering and Technology

D-Index
45
Citations
9744
World Ranking
5388
National Ranking
84

Overview

Daniel Kuhn is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research spans the fields of Decision Sciences and Engineering, with a strong emphasis on Management Science and Operations Research, Control and Systems Engineering, Electrical and Electronic Engineering, Artificial Intelligence, and Statistics and Probability.

The scientist's primary research topics include:

  • Risk and Portfolio Optimization
  • Probabilistic and Robust Engineering Design
  • Electric Power System Optimization
  • Auction Theory and Applications
  • Point processes and geometric inequalities
  • Water resources management and optimization
  • Energy, Environment, and Transportation Policies

Daniel Kuhn's recent publications include:

  • "Energy and reserve dispatch with distributionally robust joint chance constraints," 2021, published in Operations Research Letters
  • "Technical Note-Data-Driven Chance Constrained Programs over Wasserstein Balls," 2022, published in Operations Research
  • "Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization," 2021, published in Mathematics of Operations Research
  • "Robust multidimensional pricing: separation without regret," 2021, published in Mathematical Programming
  • "On linear optimization over Wasserstein balls," 2021, published in Mathematical Programming

Their coauthors frequently include Bahar Taşkesen, Wolfram Wiesemann, Soroosh Shafieezadeh-Abadeh, Çağıl Koçyiğit, and Tobias Sutter.

Daniel Kuhn's work has appeared in a range of publication venues, with multiple papers published in:

  • arXiv (Cornell University)
  • Zeitschrift für Württembergische Landesgeschichte
  • Operations Research
  • Mathematical Programming
  • SSRN Electronic Journal

In addition to articles, the scientist has also contributed to book publications, including at least one book titled "Binnenkonflikte unabhängiger Stellen der Verwaltung im Regulierungs- und Kartellrecht," published by DUNCKER UND HUMBLOT eBooks in 2022.

Best Publications

  • Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations

    Peyman Mohajerin Esfahani;Daniel Kuhn

  • Distributionally Robust Convex Optimization

    Wolfram Wiesemann;Daniel Kuhn;Melvyn Sim

  • Distributionally robust joint chance constraints with second-order moment information

    Steve Zymler;Daniel Kuhn;Berç Rustem

  • Robust Markov Decision Processes

    Wolfram Wiesemann;Daniel Kuhn;Berç Rustem

  • Primal and dual linear decision rules in stochastic and robust optimization

    Daniel Kuhn;Wolfram Wiesemann;Angelos Georghiou

  • Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

    Daniel Kuhn;Peyman Mohajerin Esfahani;Viet Anh Nguyen;Soroosh Shafieezadeh-Abadeh

  • Embedding large subgraphs into dense graphs

    Daniela Kühn;Deryk Osthus

  • Distributionally robust logistic regression

    Soroosh Shafieezadeh-Abadeh;Peyman Mohajerin Esfahani;Daniel Kuhn

  • Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls

    Grani Adiwena Hanasusanto;Daniel Kuhn

  • Generalized decision rule approximations for stochastic programming via liftings

    Angelos Georghiou;Wolfram Wiesemann;Daniel Kuhn

  • K-Adaptability in Two-Stage Robust Binary Programming

    Grani Adiwena Hanasusanto;Daniel Kuhn;Wolfram Wiesemann

  • A distributionally robust perspective on uncertainty quantification and chance constrained programming

    Grani A. Hanasusanto;Vladimir Roitch;Daniel Kuhn;Wolfram Wiesemann

  • Distributionally Robust Control of Constrained Stochastic Systems

    Bart P. G. Van Parys;Daniel Kuhn;Paul J. Goulart;Manfred Morari

  • Distributionally robust multi-item newsvendor problems with multimodal demand distributions

    Grani A. Hanasusanto;Daniel Kuhn;Stein W. Wallace;Steve Zymler

  • Worst-Case Value at Risk of Nonlinear Portfolios

    Steve Zymler;Daniel Kuhn;Berç Rustem

  • Ambiguous Joint Chance Constraints Under Mean and Dispersion Information

    Grani Adiwena Hanasusanto;Vladimir Roitch;Daniel Kuhn;Wolfram Wiesemann

  • Regularization via Mass Transportation

    Soroosh Shafieezadeh-Abadeh;Daniel Kuhn;Peyman Mohajerin Esfahani

  • From data to decisions: Distributionally robust optimization is optimal

    Bart P. G. Van Parys;Peyman Mohajerin Esfahani;Daniel Kuhn

  • Maximizing the net present value of a project under uncertainty

    Wolfram Wiesemann;Daniel Kuhn;Berç Rustem

  • Data-driven inverse optimization with imperfect information

    Peyman Mohajerin Esfahani;Soroosh Shafieezadeh-Abadeh;Grani Adiwena Hanasusanto;Daniel Kuhn

Frequent Co-Authors

Berç Rustem
Berç Rustem Imperial College London
Paul J. Goulart
Paul J. Goulart University of Oxford
Wayne Luk
Wayne Luk Imperial College London
John Lygeros
John Lygeros ETH Zurich
Afzal S. Siddiqui
Afzal S. Siddiqui Stockholm University
Manfred Morari
Manfred Morari University of Pennsylvania
David G. Luenberger
David G. Luenberger Stanford University
Pierre Pinson
Pierre Pinson Technical University of Denmark
Stein W. Wallace
Stein W. Wallace Norwegian School of Economics
Peter Pietzuch
Peter Pietzuch Imperial College London

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