Daniel Kuhn
Biography
Daniel Kuhn is Professor of Operations Research at the College of Management of Technology at EPFL, where he holds the Chair of Risk Analytics and Optimization (RAO). His current research interests are focused on data-driven optimization, the development of efficient computational methods for the solution of stochastic and robust optimization problems and the design of approximation schemes that ensure their computational tractability. This work is primarily application-driven, the main application areas being engineered systems, machine learning, business analytics and finance.
Before joining EPFL, Daniel Kuhn was a faculty member in the Department of Computing at Imperial College London (2007-2013) and a postdoctoral research associate in the Department of Management Science and Engineering at Stanford University (2005-2006). He holds a PhD degree in Economics from University of St. Gallen and an MSc degree in Theoretical Physics from ETH Zurich. He serves as the area editor for continuous optimization for Operations Research and as an associate editor for several other journals including Management Science, Mathematical Programming, Mathematics of Operations Research and Operations Research Letters. He also chairs the steering committee of the Stochastic Programming Society.
Compétences
- Decision-making under uncertainty
- Stochastic programming and robust optimization
- Data-driven optimization
- Stochastic programming and robust optimization
- Data-driven optimization
Publications
Infoscience
Main publications
2019
V. A. Nguyen; S. Shafieezadeh Abadeh; M.-C. Yue; D. Kuhn; W. Wiesemann : Distributionally Optimistic Optimization Approach to Nonparametric Likelihood Approximation. 2019. Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.
V. A. Nguyen; S. Shafieezadeh Abadeh; M.-C. Yue; D. Kuhn; W. Wiesemann : Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization. 2019. Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.
D. Kuhn; P. Mohajerin Esfahani; V. A. Nguyen; S. Shafieezadeh Abadeh : Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning; INFORMS TutORials in Operations Research. 2019. DOI : 10.1287/educ.2019.0198.
E. de Klerk; D. Kuhn; K. Postek : Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms; Mathematical Programming. 2019. DOI : 10.1007/s10107-019-01429-5.
S. Shafieezadeh Abadeh; D. Kuhn; P. Mohajerin Esfahani : Regularization via Mass Transportation; Journal of Machine Learning Research. 2019.
N. Rujeerapaiboon; K. Schindler; D. Kuhn; W. Wiesemann : Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization; SIAM Journal on Optimization. 2019. DOI : 10.1137/17M1150670.
E. Delage; D. Kuhn; W. Wiesemann : "Dice"-sion Making under Uncertainty: When Can a Random Decision Reduce Risk?; Management Science. 2019. DOI : 10.1287/mnsc.2018.3108.
2018
C. Ordoudis; V. A. Nguyen; D. Kuhn; P. Pinson : Energy and Reserve Dispatch with Distributionally Robust Joint Chance Constraints. 2018.
S. Shafieezadeh Abadeh; V. A. Nguyen; D. Kuhn; P. Mohajerin Esfahani : Wasserstein Distributionally Robust Kalman Filtering. 2018. Neural Information Processing Systems, Montréal, Canada, December 2-8, 2018.
N. Rujeerapaiboon; B. R. Barmish; D. Kuhn : On Risk Reduction in Kelly Betting Using the Conservative Expected Value. 2018. 57th IEEE Conference on Decision and Control, Miami Beach, Florida, USA, December 17-19, 2018. p. 5801-5806. DOI : 10.1109/CDC.2018.8619186.
Z. Chen; D. Kuhn; W. Wiesemann : Data-Driven Chance Constrained Programs over Wasserstein Balls; -. 2018.
C. Kocyigit Yalcin; N. Rujeerapaiboon; D. Kuhn : Robust Multidimensional Pricing: Separation without Regret; -. 2018.
V. A. Nguyen; D. Kuhn; P. Mohajerin Esfahani : Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator; -. 2018.
C. Kocyigit; G. Iyengar; D. Kuhn; W. Wiesemann : Distributionally Robust Mechanism Design; Management Science. 2018.
P. Mohajerin Esfahani; T. Sutter; D. Kuhn; J. Lygeros : From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming; SIAM Journal on Optimization. 2018. DOI : 10.1137/17M1133087.
N. Rujeerapaiboon; K. Schindler; D. Kuhn; W. Wiesemann : Scenario Reduction Revisited: Fundamental Limits and Guarantees; Mathematical Programming. 2018. DOI : 10.1007/s10107-018-1269-1.
I. Yanikoglu; D. Kuhn : Decision Rule Bounds for Two-Stage Stochastic Bilevel Programs; SIAM Journal on Optimization. 2018. DOI : 10.1137/16M1098486.
G. Hanasusanto; D. Kuhn : Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls; Operations Research. 2018. DOI : 10.1287/opre.2017.1698.
N. Rujeerapaiboon; D. Kuhn; W. Wiesemann : Chebyshev Inequalities for Products of Random Variables; Mathematics of Operations Research. 2018. DOI : 10.1287/moor.2017.0888.
P. Mohajerin Esfahani; S. Shafieezadeh Abadeh; G. A. Hanasusanto; D. Kuhn : Data-Driven Inverse Optimization with Incomplete Information; Mathematical Programming. 2018. DOI : 10.1007/s10107-017-1216-6.
P. Mohajerin Esfahani; D. Kuhn : Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations; Mathematical Programming. 2018. DOI : 10.1007/s10107-017-1172-1.
A. Georghiou; W. Wiesemann; D. Kuhn : The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications; Computational Management Science. 2018. DOI : 10.1007/s10287-018-0338-5.
2017
B. P. Van Parys; P. Mohajerin Esfahani; D. Kuhn : From Data to Decisions: Distributionally Robust Optimization is Optimal; -. 2017.
G. Consigli; D. Kuhn; P. Brandimarte : Optimal Financial Decision Making Under Uncertainty; Optimal Financial Decision Making under Uncertainty; Springer International Publishing, 2017. p. 255-290.
G. A. Hanasusanto; V. Roitch; D. Kuhn; W. Wiesemann : Ambiguous Joint Chance Constraints under Mean and Dispersion Information; Operations Research. 2017. DOI : 10.1287/opre.2016.1583.
2016
D. Lauinger; P. Caliandro; J. Van Herle; D. Kuhn : A linear programming approach to the optimization of residential energy systems; Journal of Energy Storage. 2016. DOI : 10.1016/j.est.2016.04.009.
G. A. Hanasusanto; D. Kuhn; W. Wiesemann : K-Adaptability in Two-Stage Distributionally Robust Binary Programming; Operations Research Letters. 2016. DOI : 10.1016/j.orl.2015.10.006.
G. A. Hanasusanto; D. Kuhn; W. Wiesemann : A Comment on “Computational Complexity of Stochastic Programming Problems”; Mathematical Programming. 2016. DOI : 10.1007/s10107-015-0958-2.
N. Rujeerapaiboon; D. Kuhn; W. Wiesemann : Robust Growth-Optimal Portfolios; Management Science. 2016. DOI : 10.1287/mnsc.2015.2228.
B. P. Van Parys; D. Kuhn; P. J. Goulart; M. Morari : Distributionally Robust Control of Constrained Stochastic Systems; IEEE Transactions on Automatic Control. 2016. DOI : 10.1109/TAC.2015.2444134.
B. P. G. Van Parys; P. J. Goulart; D. Kuhn : Generalized Gauss Inequalities via Semidefinite Programming; Mathematical Programming. 2016. DOI : 10.1007/s10107-015-0878-1.
2015
G. Consigli; P. Brandimarte; D. Kuhn : Financial Optimization: Optimization Paradigms and Financial Planning under Uncertainty; OR Spectrum. 2015. DOI : 10.1007/s00291-015-0406-y.
S. Shafieezadeh Abadeh; P. Mohajerin Esfahani; D. Kuhn : Distributionally Robust Logistic Regression. 2015. Neural Information Processing Systems, Montréal, Canada, December 7-12, 2015.
E. Gutin; D. Kuhn; W. Wiesemann : Interdiction Games on Markovian PERT Networks; Management Science. 2015. DOI : 10.1287/mnsc.2014.1973.
G. A. Hanasusanto; V. Roitch; D. Kuhn; W. Wiesemann : A Distributionally Robust Perspective on Uncertainty Quantification and Chance Constrained Programming; Mathematical Programming. 2015. DOI : 10.1007/s10107-015-0896-z.
W. Wiesemann; D. Kuhn : The Stochastic Time-Constrained Net Present Value Problem; Handbook on Project Management and Scheduling Vol. 2; Springer International Publishing, 2015. p. 753-780.
G. A. Hanasusanto; D. Kuhn; W. Wiesemann : K-Adaptability in Two-Stage Robust Binary Programming; Operations Research. 2015. DOI : 10.1287/opre.2015.1392.
A. Georghiou; W. Wiesemann; D. Kuhn : Generalized Decision Rule Approximations for Stochastic Programming via Liftings; Mathematical Programming. 2015. DOI : 10.1007/s10107-014-0789-6.
G. A. Hanasusanto; D. Kuhn; S. W. Wallace; S. Zymler : Distributionally Robust Multi-Item Newsvendor Problems with Multimodal Demand Distributions; Mathematical Programming. 2015. DOI : 10.1007/s10107-014-0776-y.
2014
W. Wiesemann; D. Kuhn; M. Sim : Distributionally Robust Convex Optimization; Operations Research. 2014. DOI : 10.1287/opre.2014.1314.
2013
G. A. Hanasusanto; D. Kuhn : Robust Data-Driven Dynamic Programming. 2013. Neural Information Processing Systems, Lake Tahoe, USA, December 2013.
S. Zymler; D. Kuhn; B. Rustem : Distributionally Robust Joint Chance Constraints with Second-Order Moment Information; Mathematical Programming. 2013. DOI : 10.1007/s10107-011-0494-7.
S. Zymler; D. Kuhn; B. Rustem : Worst-Case Value at Risk of Nonlinear Portfolios; Management Science. 2013. DOI : 10.1287/mnsc.1120.1615.
W. Wiesemann; D. Kuhn; B. Rustem : Robust Markov Decision Processes; Mathematics of Operations Research. 2013. DOI : 10.1287/moor.1120.0566.
P. Rocha; D. Kuhn : A Polynomial-Time Solution Scheme for Quadratic Stochastic Programs; Journal of Optimization Theory and Applications. 2013. DOI : 10.1007/s10957-012-0264-6.
2012
R. Hochreiter; D. Kuhn : Guest Editorial: Special Issue on Optimal Decision Making under Uncertainty; Computational Management Science. 2012. DOI : 10.1007/s10287-011-0136-9.
C. Gavriel; G. A. Hanasusanto; D. Kuhn : Risk-averse shortest path problems. 2012. 2012 IEEE 51st Annual Conference on Decision and Control (CDC), Maui, HI, USA, December 10-13, 2012. p. 2533-2538. DOI : 10.1109/CDC.2012.6426188.
W. Wiesemann; D. Kuhn; B. Rustem : Robust resource allocations in temporal networks; Mathematical Programming. 2012. DOI : 10.1007/s10107-011-0478-7.
W. Wiesemann; D. Kuhn; B. Rustem : Multi-resource allocation in stochastic project scheduling; Annals of Operations Research. 2012. DOI : 10.1007/s10479-008-0486-z.
P. Vayanos; D. Kuhn; B. Rustem : A constraint sampling approach for multi-stage robust optimization; Automatica. 2012. DOI : 10.1016/j.automatica.2011.12.002.
S. A. Spacey; W. Wiesemann; D. Kuhn; W. Luk : Robust Software Partitioning with Multiple Instantiation; INFORMS Journal on Computing. 2012. DOI : 10.1287/ijoc.1110.0467.
P. Rocha; D. Kuhn : Multistage stochastic portfolio optimisation in deregulated electricity markets using linear decision rules; European Journal of Operational Research. 2012. DOI : 10.1016/j.ejor.2011.08.001.
D. Bampou; D. Kuhn : Polynomial Approximations for Continuous Linear Programs; SIAM Journal on Optimization. 2012. DOI : 10.1137/110822992.
2011
M. J. Hadjiyiannis; P. Goulart; D. Kuhn : An Efficient Method to Estimate the Suboptimality of Affine Controllers; IEEE Transactions on Automatic Control. 2011. DOI : 10.1109/TAC.2011.2139390.
D. Kuhn : Guest Editorial: Special Issue on Computational Finance; Computational Management Science. 2011. DOI : 10.1007/s10287-009-0112-9.
E. Kalyvianaki; W. Wiesemann; Q. H. Vu; D. Kuhn; P. Pietzuch : SQPR: Stream query planning with reuse. 2011. 2011 IEEE International Conference on Data Engineering (ICDE 2011), Hannover, Germany, 11-16 04 2011. p. 840-851. DOI : 10.1109/ICDE.2011.5767851.
F. Kong; D. Kuhn; B. Rustem : Welfare-Maximizing Correlated Equilibria with an Application to Wireless Communication. 2011. 18th IFAC World Congress, Università Cattolica del Sacro Cuore, Milano, Italy, August 2011. p. 8920-8925. DOI : 10.3182/20110828-6-IT-1002.02982.
P. Vayanos; W. Wiesemann; D. Kuhn : Hedging Electricity Swing Options in Incomplete Markets. 2011. 18th IFAC World Congress, Università Cattolica del Sacro Cuore, Milano, Italy, August 2011. p. 846-853. DOI : 10.3182/20110828-6-IT-1002.03528.
M. J. Hadjiyiannis; P. J. Goulart; D. Kuhn : A scenario approach for estimating the suboptimality of linear decision rules in two-stage robust optimization. 2011. 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), Orlando, FL, USA, 12-15 December 2011. p. 7386-7391. DOI : 10.1109/CDC.2011.6161342.
P. Vayanos; D. Kuhn; B. Rustem : Decision rules for information discovery in multi-stage stochastic programming. 2011. 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), Orlando, FL, USA, December 12-15, 2011. p. 7368-7373. DOI : 10.1109/CDC.2011.6161382.
D. Bampou; D. Kuhn : Scenario-free stochastic programming with polynomial decision rules. 2011. 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), Orlando, FL, USA, December 12-15, 2011. p. 7806-7812. DOI : 10.1109/CDC.2011.6161150.
K. Frauendorfer; D. Kuhn; M. Schürle : Barycentric Bounds in Stochastic Programming: Theory and Application; Stochastic Programming: The State of the Art, In Honor of George B. Dantzig; New York, NY: Springer New York, 2011. p. 67-96.
S. Zymler; B. Rustem; D. Kuhn : Robust portfolio optimization with derivative insurance guarantees; European Journal of Operational Research. 2011. DOI : 10.1016/j.ejor.2010.09.027.
D. Kuhn; W. Wiesemann; A. Georghiou : Primal and dual linear decision rules in stochastic and robust optimization; Mathematical Programming. 2011. DOI : 10.1007/s10107-009-0331-4.
2010
F. W. Kong; D. Kuhn; B. Rustem : A cutting-plane method for Mixed-Logical Semidefinite Programs with an application to multi-vehicle robust path planning. 2010. 2010 49th IEEE Conference on Decision and Control (CDC), Atlanta, GA, USA, December 15-17, 2010. p. 1360-1365. DOI : 10.1109/CDC.2010.5717988.
R. Fonseca; D. Kuhn; B. Rustem : Linearly Adjustable International Portfolios. 2010. ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics, Rhodes, Greece, September 19–25, 2010. p. 338-341. DOI : 10.1063/1.3498469.
W. Wiesemann; D. Kuhn; B. Rustem : Maximizing the net present value of a project under uncertainty; European Journal of Operational Research. 2010. DOI : 10.1016/j.ejor.2009.05.045.
D. Kuhn; D. G. Luenberger : Analysis of the rebalancing frequency in log-optimal portfolio selection; Quantitative Finance. 2010. DOI : 10.1080/14697680802629400.
2009
S. A. Spacey; W. Luk; P. H. J. Kelly; D. Kuhn : Rapid Design Space visualisation through hardware/software partitioning. 2009. 2009 5th Southern Conference on Programmable Logic (SPL), São Carlos, Brazil, 1-3 04 2009. p. 159-164. DOI : 10.1109/SPL.2009.4914913.
D. Kuhn; P. Parpas; B. Rustem; R. Fonseca : Dynamic Mean-Variance Portfolio Analysis under Model Risk; Journal of Computational Finance. 2009. DOI : 10.21314/JCF.2009.202.
D. Kuhn : Convergent Bounds for Stochastic Programs with Expected Value Constraints; Journal of Optimization Theory and Applications. 2009. DOI : 10.1007/s10957-008-9476-1.
D. Kuhn : An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous Time; Mathematics of Operations Research. 2009. DOI : 10.1287/moor.1080.0369.
G. Haarbrücker; D. Kuhn : Valuation of electricity swing options by multistage stochastic programming; Automatica. 2009. DOI : 10.1016/j.automatica.2008.11.022.
2008
W. Wiesemann; R. Hochreiter; D. Kuhn : A Stochastic Programming Approach for QoS-Aware Service Composition. 2008. 2008 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid), Lyon, France, 19-22 05 2008. p. 226-233. DOI : 10.1109/CCGRID.2008.40.
D. Kuhn; P. Parpas; B. Rustem : Stochastic Optimization of Investment Planning Problems in the Electric Power Industry; Energy Systems Engineering; Weinheim: Wiley-VCH, 2008. p. 215-230.
D. Kuhn; P. Parpas; B. Rustem : Threshold Accepting Approach to Improve Bound-based Approximations for Portfolio Optimization; Computational Methods in Financial Engineering; Berlin: Springer Verlag, 2008. p. 3-26.
D. Kuhn; P. Parpas; B. Rustem : Bound-based decision rules in multistage stochastic programming; Kybernetika. 2008.
D. Kuhn : Aggregation and discretization in multistage stochastic programming; Mathematical Programming. 2008. DOI : 10.1007/s10107-006-0048-6.
2005
K. Frauendorfer; J. Güssow; G. Haarbrücker; D. Kuhn : Stochastische Optimierung im Energiehandel: Entscheidungsunterstützung und Bewertung für das Portfoliomanagement. 2005.
K. Frauendorfer; G. Haarbrücker; K. Kiske; D. Kuhn : Swing-Optionen im Elektrizitätsmarkt – Bewertung und optimale Ausübungsstrategien komplexer Stromderivate. 2005.
D. Kuhn : Numerical Methods to Increase the Value Added. 2005. Energy Talks Ossiach '05, Ossiach, Austria, April 13-15, 2005.
D. Kuhn : Generalized Bounds for Convex Multistage Stochastic Programs ; Berlin: Springer-Verlag.
2003
G. Haarbrücker; D. Kuhn : A Software Tool for the Valuation and Optimal Exercise of Swing Options. 2003.
K. Frauendorfer; J. Güssow; D. Kuhn : Energy Business and Finance Policy - Parallels in Methodology and Duties. 2003. 4. Internationales Energiesymposium, Fuschl, Salzburger Land, Austria, September 25, 2003. p. 124-137.
2002
K. Frauendorfer; J. Güssow; G. Haarbrücker; D. Kuhn; G. Ostermaier : Umsetzung stochastischer Optimierungsmethoden in der Energiewirtschaft. 2002. VDI Tagung "IT-Lösungen für die Energiewirtschaft in liberalisierten Märkten", Schliersee, DE, May 15, 2002. p. 141-151.
2001
D. Kuhn; N. Chtchelkatchev; G. Lesovik; G. Blatter : Supercurrents through gated superconductor–normal-metal–superconductor contacts: The Josephson transistor; Physical Review B. 2001. DOI : 10.1103/PhysRevB.63.054520.
