Curiculum Vita :(pdf)
Welcome to my personal web page. This site will eternally be in evolution, but please enjoy what is currently available.
I am professor at HEC Montréal in the department of Decision Sciences. I graduated in 2009 with a Ph.D. in Electrical Engineering from Stanford University. During my stay at Stanford, I had the opportunity to work with Prof. Andrew Y. Ng, Prof. Shie Mannor, and Prof. Yinyu Ye. My thesis presented new optimization models for taking into account parameter and distribution uncertainty in a range of decision problems where the knowledge of some parameters is limited to historical samples.
Since I joined HEC Montréal, I have entertained a strong interest for quantitative methodologies that can help manage the risks related to market, environmental or physical uncertainty that is present in industrial and financial decision problems. Specifically, my research interests span the areas of optimization, decision analysis, artificial intelligence and applied statistics. I am especially fascinated about how concept of robust optimization can successfully reconcile the design of a decision model with the prevailing ambiguity about outcomes and about how these might be perceived by the decision maker. Applications that have caught my attention include, but are not limited to, portfolio selection, e-commerce, resource allocation, network routing, inventory management and energy production problems.
Delage, E., “Quantitative Risk Management Using Robust Optimization”, offered at HEC Montréal , Fall 2016, Fall 2017, Fall 2019, next in Winter 2021. (lecture notes, some course material, and short intro docs)
Delage, E., “Quantitative Risk Management Using Robust Optimization”, offered at EPFL , Summer 2015.
Editorial work :
E. Delage, D. Iancu, Special Issue: Robust Optimization and Applications, Computational Management Science, March 2016. (link to issue)
Working drafts :
S. A. Sani, O. Bahn, E. Delage, R. F. Tchuendom, Robust Integration of Electric Vehicles Charging Load in Smart Grid's Capacity Expansion Planning, working draft (pdf)
A. Fathan, E. Delage, Deep Reinforcement Learning for Optimal Stopping with Application in Financial Engineering, working draft. (pdf)
V. A. Nguyen, F. Zhang, J. Blanchet, E. Delage, Y. Ye, Robustifying Conditional Portfolio Decisions via Optimal Transport, working draft. (pdf)
C. Nicolas, S. Tchung-Ming, O. Bahn, E. Delage, Robust Energy Transition Pathways for Global Warming Targets, working draft. (pdf)
F. Zhang, V. A. Nguyen, J. Blanchet, E. Delage, Y. Ye, Distributionally Robust Local Non-parametric Conditional Estimation, NeurIPS, 2020. (pdf)
F. Rodrigues, A. Agra, C. Requejo, E. Delage, Lagrangian Duality for Robust Problems with Decomposable Functions: The Case of a Robust Inventory Problem, INFORMS Journal on Computing, 33(2):685-705,2021. (pdf, link to article)
A. Ardestani-Jaafari, E. Delage, Linearized Robust Counterparts of Two-stage Robust Optimization Problem with Applications in Operations Management, accepted in INFORMS Journal on Computing. (pdf, matlab code, link to article)
C. Peng, E. Delage, J. Li, Probabilistic Envelope Constrained Multiperiod Stochastic Emergency Medical Services Location Model and Decomposition Scheme, Transportation Science, 54(6):1471-1494. (pdf, link to article)
T. Bazier-Matte, E. Delage, Generalization Bounds for Regularized Portfolio Selection with Market Side Information, INFOR: Information Systems and Operational Research, 58(2):374-401, 2020. (pdf, link to article)
A. Hajebrahimi, I. Kamwa, E. Delage, M. Abdelaziz, Adaptive Distributionally Robust Optimization for Electricity and Electrified Transportation Planning, IEEE Transactions on Smart Grid, 11(5):4278-4289, 2020. (link to article)
A. Barbry, M. F. Anjos, E. Delage, Robust Self-Scheduling of a Price-Maker Energy Storage Facility in the New York electricity market, Energy Economics, 78:629-646, 2019. (link to article, tech report)
C. Gauvin, E. Delage, M. Gendreau, A Successive Linear Programming Algorithm with Non-Linear Time Series for the Reservoir Management Problem, Computational Management Science, Vol. 15, No. 1, pp 55-86, 2018. (link to article, tech report)
C. Gauvin, E. Delage, M. Gendreau, A Stochastic Program with Tractable Time Series and Affine Decision Rules for the Reservoir Management Problem, European Journal of Operational Research, Vol. 267, No. 2, pp 716-732, 2018. (link to article, tech report)
E. Delage, L. G. Gianoli, B. Sansò, A Practicable Robust Counterpart Formulation for Decomposable Functions: A Network Congestion Case Study, Operations Research, Vol 66, No. 2, pp. 535-567, 2018. (link to article, tech report)
E. Delage, J. Y. Li, Minimizing Risk Exposure when the Choice of a Risk Measure is Ambiguous, Management Science, Vol. 64, No. 1, pp. 327-344, 2018. (link to article)
A. Ardestani-Jaafari, E. Delage, The Value of Flexibility in Robust Location-transportation Problems, Transportation Science, Vol. 52, No. 1, pp 189-209, 2018. (link to article)(*Honorable mention at CORS best student paper competition 2016*)
C. Gauvin, E. Delage, M. Gendreau, Decision rule approximations for the risk averse reservoir management problem, European Journal of Operational Research, Vol. 261, No. 1, pp. 317-336, 2017. (tech report, link to article)
A. Ardestani-Jaafari, E. Delage, Affinely Adjustable Robust Location Transportation Problem, Proceedings of the 2014 Industrial and Systems Engineering Research Conference. (pdf)
A. Ardestani-Jaafari, E. Delage, Robust Optimization of Sums of Piecewise Linear Functions with Application to Inventory Problems, Operations Research, Vol. 62, No. 2, pp 474-494, 2016. (link to article, slides)
B. Armbruster, E. Delage, Decision Making under Uncertainty when Preference Information is Incomplete, Management Science, Vol. 61, No. 1, pp. 111-128, 2015. (link to article)
J. Cheng, E. Delage, A. Lisser, Distributionally Robust Stochastic Knapsack Problem, SIAM Journal on Optimization, Vol. 24, No. 3, pp. 1485-1506, 2014. (pdf)
E. Delage, S. Arroyo, Y. Ye, The Value of Stochastic Modeling in Two-Stage Stochastic Programs with Cost Uncertainty, Operations Research, Vol. 62, No. 6, pp. 1377-1393, 2014. (link to article, e-companion)
J. G. Carlsson, E. Delage, Robust Partitioning for Stochastic Multi-Vehicle Routing, Operations Research, Vol. 61, No. 3, pp. 727-744, 2013. (link to article)
S. Agrawal, E. Delage, M. Peters, Z. Wang, Y. Ye, A Unified Framework for Dynamic Prediction Market Design, Operations Research, Vol. 59, No. 3, pp. 550-568, 2011. (link to article)
Delage E., Ye Y. Distributionally Robust Optimization under Moment Uncertainty with Application to Data-Driven Problems, Operations Research, Vol. 58, No. 3, pp. 596-612, 2010. 1st place Nicholson Award 2008 (link to article, summary of contribution)
Delage E., Mannor S. Percentile Optimization in Uncertain MDP with Application to Efficient Exploration, ICML 2007. (pdf)
Delage E., Mannor S. Percentile Optimization for MDP with Parameter Uncertainty, Operations Research, Vol. 58, No.1, pp. 203-213, 2010. Finalist for Nicholson Award 2007. (link to article, summary of contribution)
Labs J., Delage E., Ullman R., Beaton G. (2003) “Synchronizing Method and Apparatus” (Patent CA 2433139, US 7352778, US 20040264510).
Labs J., Gagnon S., Delage E. (2003) “Method and apparatus for estimating frequency offsets for an OFDM burst receiver”. (Patent US 20040264584).
Delage, E., “Webinar November 2019 : Discover our PhD in Management Science ”, presented at HEC Montreal, November 4, 2019.
Delage, E. (joint work with S. Guo and H. Xu), “Preference Robust Utility-based Shortfall Risk Minimization” (video), presented at Workshop on Robust Optimization, Avignon, 2018.
Delage, E. (joint work with W. Wiesemann and D. Kuhn), “Dice-sion Making under Uncertainty: When Can a Random Decision Reduce Risk?”, presented at IFORS 2017, EUROPT 2017.
Delage, E. (joint work with A. Ardestani-Jaafari), “Linear and Conic Programming Reformulations of Two-Stage Robust Linear Programs”, presented at Workshop on Modern Convex Optimization, 5th of July 2017.
Delage, E. (joint work with B. Armbruster and J. Y. Li), “Preference Robust Optimization for Decision Making under Uncertainty”, presented at ICCOPT 2016, 10th of August 2016.
Delage, E., “The Value of Distribution Information in Distributionally Robust Optimization”, presented at EURANDOM Workshop on Robust Optimization in Applied Probability , 9th of November 2015.
Delage, E. (joint work with A. Ardestani-Jaafari), “Linearized Robust Counterparts of Two-Stage Distribution Problems”, presented at EPFL , 22nd of July 2015.
Delage, E., “Addressing Model Ambiguity in the Expected Utility Framework”, presented at BFG Conf. on Opt. (June 2015), at GERAD (February 2015), at OR Center Seminar, MIT (November 2014), and at Rotman School of Management (December 2012).
Delage, E. (joint work with A. Ardestani-Jaafari)“Yet Another Tractable Approximation for Robust Optimization”, presented at INFORMS Annual Meeting, October 2013.
Delage, E. (joint work with S. Arroyo and Y. Ye)“The Value of Stochastic Modeling in Two-Stage Stochastic Programs”, presented at INFORMS Annual Meeting, October 2013.
Delage, E. (joint work with J. Y. Li)“Accounting for Risk Measure Ambiguity when Optimizing Financial Positions”, presented at ICSP, July 2013.
Delage, E., “Untying the Knot between a Stochastic Program and its Distribution”, presented at University of Toronto, August 2011.
Delage, E., “Distributionally Robust Optimization under Moment Uncertainty with Application to Data-Driven Problems”, presented at INFORMS annual meeting 2008.
Delage, E., “Data-Driven Optimization for Portfolio Selection”, presented at INFORMS annual meeting 2008.
Delage, E., “”, presented at INFORMS annual meeting 2008.
Delage, E., “”, presented at INFORMS annual meeting 2007.
Delage, E., “Percentile Optimization in Uncertain MDP with Application to Efficient Exploration”. presented at ICML 2007.
Delage, E., “A Dynamic Bayesian Network Model for Autonomous 3d Reconstruction from a Single Indoor Image”. Poster presented at CVPR 2006.
Supervised students and students collaborators :
Open positions :
I am searching for graduate students that are either interested in developing new applications for techniques that can help handle uncertainty in decision problems or wish to contribute to the development of new methodologies. Those that are interested should email me their resume and a brief explanation of what they are interested in. (email@example.com, Ph.D. program details)
Updated: May 31st, 2021Total number of visits: