meErick Delage

Canada Research Chair in Decision Making under Uncertainty

Member of the College of New Scholars, Artists and Scientists of the Royal Society of Canada

Professor, Department of Decision Sciences, HEC Montréal

Member of GERAD

Associate Academic Member of MILA

Address:

HEC Montréal
3000, chemin de la Côte-Sainte-Catherine
Montréal (Québec)
Canada H3T 2A7

Email:
erick.delage@hec.ca
Phone: 514 340-7040
Fax: 514 340-5634
Office: 4.315
Github: url

 

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 robust and stochastic optimization, decision theory, machine learning, reinforcement learning, and risk management with applications to portfolio optimization, inventory management, energy and transportation problems.

 

I recently took the leadership with Emma Frejinger and Yossiri Adulyasak of an ambitious research program entitled Integrated Machine Learning and Optimization for Decision Making under Uncertainty and supported by IVADO's strategic research funding program. The program aims at developing new methods for making the most effective and adaptive use of data in decision-making. It is founded on modern optimization and machine learning perspectives that encompasses developments in deep reinforcement/end-to-end learning, risk averse decision theory, and contextual/distributionally robust optimization. Don't hesitate to get in touch if you wish to get involved.

 

Courses :

 

Delage, E., “Quantitative Risk Management Using Robust Optimization”, offered at HEC Montréal , Fall 2016, Fall 2017, Fall 2019, Winter 2021, Winter 2022, Winter 2023. (course description, lecture notes, some course material, and short intro docs)

 

Delage, E., “Decision Analysis”, offered at HEC , Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020, Winter 2022, Fall 2022. (lecture notes, inclass EN, inclass FR)

 

Delage, E., “Robust Optimization”, offered at Politecnico di Milano , Winter 2024.

 

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 :

 

X. Wang, O. Arslan, J.-F. Cordeau, E. Delage, Network Design for Ultra-fast Delivery Services via Probabilistic Envelope Constrained Programs, working draft. (SSRN)

 

U. Sadana, A. Chenreddy, E. Delage, A. Forel, E. Frejinger, T. Vidal, A Survey of Contextual Optimization Methods for Decision Making under Uncertainty, working draft. (arxiv)

 

M. Poursoltani, E. Delage, A. Georghiou, Robust Data-driven Prescriptiveness Optimization, working draft. (arxiv)

 

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. (arxiv)

 

Publications :

 

X. Wang, O. Arslan, E. Delage, Crowdkeeping in Last-mile Delivery, accepted in Transportation Science. (pdf)

 

S. Marzban, E. Delage, J. Y. Li, J. Desgagne-Bouchard, C. Dussault, WaveCorr: Deep Reinforcement Learning with Permutation Invariant Policy Networks for Portfolio Management, Operations Research Letters, 51(6):680-686, 2023. (open access journal version)

 

J. L. Hau, E. Delage, M. Ghavamzadeh, M. Petrik, On Dynamic Program Decompositions of Static Risk Measures, accepted NeurIPS 2023. (arxiv)

 

S. Wang, E. Delage, A Column Generation Scheme for Distributionally Robust Multi-Item Newsvendor Problems, INFORMS Journal on Computing. (pdf, journal version)

 

S. Marzban, E. Delage, Jonathan Y. Li, Deep Reinforcement Learning for Equal Risk Pricing and Hedging under Dynamic Expectile Risk Measures, Quantitative Finance. (pdf, slides, journal version)

 

H. Li, E. Delage, N. Zhu, M. Pinedo, S. Ma, Distributional Robustness and Inequity Mitigation in Disaster Preparedness of Humanitarian Operations, accepted in Manufacturing & Service Operations Management. (pdf, journal version)

 

A. Ghahtarani, A. Saif, A. Ghasemi, E. Delage, A Double-oracle, Logic-based Benders decomposition approach to solve the K-adaptability problem, Computers and Operations Research, 155:106243, 2023. (journal version, pdf)

 

M. Poursoltani, E. Delage, A. Georghiou, Risk-averse Regret Minimization in Multi-stage Stochastic Programs, accepted in Operations Research. (journal version, pdf)

 

A. Chenreddy, N. Bandi, E. Delage, Data-Driven Conditional Robust Optimization, NeurIPS, 2022. (conference version, pdf)

 

R. Fan, E. Delage, Risk-Aware Bid Optimization for Online Display Advertisement, Proceedings of 31st ACM International Conference on Information and Knowledge Management, 457-467, 2022. (conference version, pdf)

 

C. Peng, E. Delage, Data-Driven Optimization with Distributionally Robust Second-Order Stochastic Dominance Constraints, accepted in Operations Research. (journal version, pdf, video, slides)

 

U. Sadana, E. Delage, The Value of Randomized Strategies in Distributionally Robust Risk Averse Network Interdiction Problems, INFORMS Journal on Computing, 35:1, 216-232, 2023. (journal version, pdf, video, slides)

 

S. A. Sani, O. Bahn, E. Delage, R. F. Tchuendom, Robust Integration of Electric Vehicles Charging Load in Smart Grid's Capacity Expansion Planning, Dynamic Games and Applications, 12, 1010-1041, 2022. (journal version, pdf)

 

S. Aliakbari Sani, A. Maroufmashat, F. Babonneau, O. Bahn, E. Delage, A. Haurie, N Mousseau, K Vaillancourt, Energy Transition Pathways for Deep Decarbonization of the Greater Montreal Region: An Energy Optimization Framework , Energies, 15(10):3760, 2022. (journal version)

 

C. Nicolas, S. Tchung-Ming, O. Bahn, E. Delage, Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty , Energies, 14(24):8595, 2021. (journal version, pdf)

 

S. Aliakbari Sani, O. Bahn, E. Delage, Affine Decision Rule Approximation to Immunize against Demand Response Uncertainty in Smart Grids' Capacity Planning, European Journal of Operational Research. (pdf, video, slides, journal version)

 

E. Delage, S. Guo, H. Xu, Shortfall Risk Models When Information of Loss Function Is Incomplete, Operations Research. (pdf, video, slides, journal version)

 

M. Poursoltani, E. Delage, Adjustable Robust Optimization Reformulations of Two-Stage Worst-case Regret Minimization Problems, Operations Research. (pdf, video, slides, journal version)

 

S. Marzban, E. Delage, J. Y. Li, Equal Risk Pricing and Hedging of Financial Derivatives with Convex Risk Measures, Quantitative Finance, 22(1):47-73, 2022. (pdf, video, slides, journal version)

 

V. A. Nguyen, F. Zhang, J. Blanchet, E. Delage, Y. Ye, Distributionally Robust Local Non-parametric Conditional Estimation, NeurIPS, 2020. (pdf)

 

E. Delage, A. Saif, The Value of Randomized Solutions in Mixed-Integer Distributionally Robust Optimization Problems, INFORMS Journal on Computing, 34(1):333-353, 2022. (pdf, video, slides, journal version)

 

A. Saif, E. Delage, Data-Driven Distributionally Robust Capacitated Facility Location Problem, European Journal of Operational Research, 291(3):995-1007,2021. (pdf, journal version)

 

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, journal version)

 

A. Ardestani-Jaafari, E. Delage, Linearized Robust Counterparts of Two-stage Robust Optimization Problem with Applications in Operations Management, INFORMS Journal on Computing, 33(3):1138-1161, 2021. (pdf, matlab code, journal version)

 

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, 2020. (pdf, journal version)

 

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, journal version)

 

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. (journal version)

 

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. (journal version, tech report)

 

E. Delage, D. Kuhn, W. Wiesemann, "Dice"-sion Making under Uncertainty: When Can a Random Decision Reduce Risk?, Management Science, 65(7):3282-3301, 2019. (journal version, video, slides)

 

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. (journal version, 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. (journal version, 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. (journal version, 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. (journal version)

 

A. Ardestani-Jaafari, E. Delage, The Value of Flexibility in Robust Location-transportation Problems, Transportation Science, Vol. 52, No. 1, pp 189-209, 2018. (journal version)(*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, journal version)

A. Ardestani-Jaafari, E. Delage, Affinely Adjustable Robust Location Transportation Problem, Proceedings of the 2014 Industrial and Systems Engineering Research Conference. (pdf)

 

M. Denault, E. Delage, J.-G. Simonato, Dynamic portfolio choice: a simulation-and-regression approach, Optimization and Engineering, Vol. 18, No. 2, pp. 369-406, 2017. (tech report, journal version)

 

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. (journal version, slides)

 

E. Delage, D. Iancu, Robust Multistage Decision Making, TutORials in Operations Research, pp. 20-46, 2015. (journal version, slides)

 

B. Armbruster, E. Delage, Decision Making under Uncertainty when Preference Information is Incomplete, Management Science, Vol. 61, No. 1, pp. 111-128, 2015. (journal version)

 

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. (journal version, e-companion)

 

J. G. Carlsson, E. Delage, Robust Partitioning for Stochastic Multi-Vehicle Routing, Operations Research, Vol. 61, No. 3, pp. 727-744, 2013. (journal version)

 

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. (journal version)

S. Agrawal, E. Delage, M. Peters, Z. Wang, Y. Ye, Unified Framework for Dynamic Pari-Mutuel Information Market Design, 10th ACM Electronic Commerce Conference. (conference version, extended version)

 

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 (journal version, summary of contribution)

 

Delage E. Regret-based Online Ranking for a Growing Digital Library, ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2009. (pdf, extra material)

 

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. (journal version, summary of contribution)

 

Delage E., Lee H. , Ng A Y (2006). A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image, CVPR 2006.  (pdf, experiments)

Delage E., Lee H., Ng A. Y. Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes, ISRR 2005.  (pdf, experiments)

 

Thesis :

 

Distributionally Robust Optimization in context of Data-driven Problems. (abstract, pdf)

 

Patents :

 

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).

 

Presentations :

 

Delage, E. (joint work with A. Chenreddy and N. Bandi), “Data-Driven Conditional Robust Optimization”, presented at ICSP Tutorial on End-to-end Learning, July, 2023.

 

Delage, E. (joint work with U. Sadana, A. Chenreddy, E. Frejinger, A. Forel, T. Vidal), “Introduction to Contextual (Stochastic) Optimization”, presented at ICSP Tutorial on End-to-end Learning, July, 2023 (INSEAD, HEC Paris).

 

Delage, E. (joint work with U. Sadana, A. Chenreddy, E. Frejinger, A. Forel, T. Vidal), “Introduction to Data-driven Contextual Stochastic Optimization”, presented at COSMO Tech Day, June, 2023.

 

Delage, E. (joint work with S. Marzban, J. Li, J. L. Hau, M. Petrik, M. Ghavamzadeh), “Deep Reinforcement Learning for Risk Averse Sequential Decision Making Problems”, presented at MILA RL Workshop, June, 2023.

 

Delage, E. (joint work with C. Peng), “Data-Driven Optimization with Distributionally Robust Second-Order Stochastic Dominance Constraints”, presented at INFORMS Annual Meeting, October, 2022.

 

Delage, E., “Webinar November 2022 : Discover our PhD in Management Science ”, presented at HEC Montreal, September, 2022.

 

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.

See also BIRS DRO workshop : video 1 (W. Wiesemann) and video 2 (E. Delage))

 

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., “Robust Partitioning for Stochastic Multi-Vehicle Routing”, presented at INFORMS annual meeting 2008.

 

Delage, E., “Percentile Optimization for Markov Decision Processes with Parameter Uncertainty”, 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. (erick.delage@hec.ca, Ph.D. program details)

 

 

Updated:  May 31st, 2021

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