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IDS Distinguished Speaker Series #6 - Professor Erick Delage from HEC Montréal

Title: Towards Robust and Risk-aware Contextual Optimization
Speaker: Prof. Erick Delage, Professor in Department of Decision Sciences, HEC Montréal
Moderator: Prof. Guodong Li, Associate Director of HKU IDS; Professor, Department of Statistics & Actuarial Science, HKU
Date: May 21, 2024
Time: 10:00am – 11:00am
Venue: Tam Wing Fan Inno Wing II / Zoom
Mode: Hybrid. Seats for on-site participants are limited. A confirmation email will be sent to participants who have successfully registered.


Recently there has been a surge of interest in operations research (OR) and the machine learning (ML) community in combining prediction algorithms and optimization techniques to solve decision-making problems in the face of uncertainty. This gave rise to the field of contextual optimization, under which data-driven procedures are developed to prescribe actions to the decision-maker that make the best use of the most recently updated information. A large variety of models and methods have been presented in both OR and ML literature under a variety of names, including data-driven optimization, prescriptive optimization, predictive stochastic programming, policy optimization, (smart) predict/estimate-then-optimize, decision-focused learning, (task-based) end-to-end learning/forecasting/optimization, etc. The first part of the talk will identify three main frameworks for learning policies from data and sort out the literature that has pioneered this emerging field. The second part of the talk will present an overview of our groups efforts towards making contextual optimization methods more robust and risk-aware.


Prof. Erick Delage
Professor @ Department of Decision Sciences, HEC Montréal

Professor Erick Delage is a professor in the Department of Decision Sciences at HEC Montréal, a chairholder of the Canada Research Chair in decision making under uncertainty, and a member of the College of New Scholars, Artists and Scientists of the Royal Society of Canada. His research interests span the areas of robust and stochastic optimization, decision analysis, reinforcement learning, and risk management with applications to portfolio optimization, inventory management, energy, and transportation problems.


Prof. Guodong Li
Associate Director @ HKU IDS; Associate Head (Research) & Professor @ Department of Statistics & Actuarial Science

Professor Guodong Li joined the Department of Statistics & Actuarial Science, The University of Hong Kong, in 2009 as an Assistant Professor, and currently is a Professor. Prior to this, Professor Li had worked at the Division of Mathematical Sciences, Nanyang Technological University, Singapore, as an Assistant Professor since he received his PhD degree in statistics from the University of Hong Kong in 2007. He got his Bachelor and Master degrees in Statistics from Peking University.

For full biography of Professor Li, please refer to:

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