PeopleofSuperintelligence

Researcher

Erick Delage

Erick Delage is a professor of decision sciences whose research connects machine learning and reinforcement learning with optimization under uncertainty. He earned a B.S. in computer engineering at McGill and completed a PhD in electrical engineering at Stanford in 2009, where he worked with Andrew Ng, Shie Mannor and Yinyu Ye. At HEC Montréal, he became a professor in 2009, held the Canada Research Chair in Decision Making Under Uncertainty from 2014 to 2025, and joined the Royal Society of Canada's College of New Scholars in 2020. His research includes deep reinforcement learning for equal-risk option pricing and hedging, a 2025 survey of contextual optimization and robust portfolio decisions, and a 2026 data-driven vehicle-routing paper. Since 2025, he holds HEC Montréal's Research Chair in Data-driven Decision Making, is a full professor in its Department of Decision Sciences, and is an associate academic member of Mila, where his research topics include optimization and reinforcement learning.

Timeline

  1. By 2009

    McGill and a Stanford PhD

    He earns a B.S. in computer engineering at McGill and completes a PhD in electrical engineering at Stanford in 2009. There, he works with Andrew Ng, Shie Mannor and Yinyu Ye.

  2. 2009

    Joining HEC Montréal

    In 2009, he joins HEC Montréal as a professor in its Department of Decision Sciences. His research spans robust and stochastic optimization, decision theory, machine learning, reinforcement learning and risk management.

  3. 2014–2025

    Canada Research Chair

    From 2014 to 2025, he holds the Canada Research Chair in Decision Making Under Uncertainty.

  4. 2020

    Royal Society membership

    In 2020, he joins the Royal Society of Canada's College of New Scholars, Artists and Scientists.

  5. 2021–2023

    Risk-aware reinforcement learning

    In 2021, he coauthors a deep reinforcement learning paper that extends an off-policy actor-critic algorithm to risk-averse Markov decision processes with dynamic expectile risk. Its 2023 journal version applies the method to equal-risk option pricing and hedging.

  6. 2025

    A contextual optimization survey

    In 2025, he coauthors A survey of contextual optimization methods for decision-making under uncertainty with Utsav Sadana, Abhilash Chenreddy, Alexandre Forel, Emma Frejinger and Thibaut Vidal. He also coauthors Robustifying Conditional Portfolio Decisions via Optimal Transport with Viet Anh Nguyen, Fan Zhang, Shanshan Wang, José Blanchet and Yinyu Ye.

  7. February 2026

    Data-driven vehicle routing

    In February 2026, he coauthors Data-Driven Stochastic Vehicle Routing Problems with Deadlines Under Decision-Dependent Travel Time with Shanshan Wang and Leandro C. Coelho. The paper is due to appear in Manufacturing & Service Operations Management in 2026.

  8. Since 2025

    HEC Montréal research chair

    Since 2025, he holds the Research Chair in Data-driven Decision Making at HEC Montréal. He is a full professor in its Department of Decision Sciences and an associate academic member of Mila, where his research topics include optimization and reinforcement learning.

Career

  1. Since 2009HEC MontréalFull professor, Canada Research Chair in Decision Making Under Uncertainty
  2. NowMilaAssociate academic member

Education

  1. 2009Stanford UniversityPhD in electrical engineering
  2. McGill UniversityB.S. in computer engineering

From the biography.

  1. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Mila. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Mila. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  3. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Mila. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Mila. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Erick Delage yet. Send us a free-licensed photo.

  1. Erick Delage's home page tintin.hec.ca. Checked 22 October 2026.
  2. Erick Delage | HEC Montréal hec.ca. Checked 22 October 2026.
  3. Alain d’Astous and Erick Delage inducted into the Royal Society of Canada | HEC Montréal hec.ca. Checked 22 October 2026.
  4. Erick Delage : GERAD gerad.ca. Checked 22 October 2026.
  5. [2109.04001] Deep Reinforcement Learning for Equal Risk Pricing and Hedging under Dynamic Expectile Risk Measures arxiv.org. Checked 22 October 2026.
  6. Erick Delage | Mila mila.quebec. Checked 22 October 2026.