Mohammed Amine Bennouna

Ph.D. Candidate
Operations Research Center
Massachusetts Institute of Technology

Contact: amineben [at]

About me

I am a 4th year doctoral candidate at the MIT Operations Research Center, advised by Prof. B. Van Parys. Prior to joining MIT, I graduated from Ecole Polytechnique in 2019 Majoring in Applied Mathematics and completed two years of preparatory program (CPGE) in Lycée Louis-le-Grand.

My research interest lies in data-driven decision-making. I strive to understand theoretically how to use most efficiently observed data to make decisions. The goal is to derive from these theoretical insights novel algorithms that tackle challenges in data-driven decision-making. My recent work focuses on designing novel robust approaches to Machine Learning problems (and more generally Stochastic Optimization) using Distributionally Robust Optimization. The goal is to understand what are the sources of overfitting (poor generalization) in data-driven stochastic optimization and design robust approaches precisely pretecting against such sources. These approaches are typically provably optimal (i.e the best that can be done with the data) when a certain out-of-sample guarantee is desired. Earlier in my PhD, I have also worked in Reinforcement Learning (RL) to introduce a novel more efficient and interepretable off-line RL framework. We have then applied this framework to COVID-19 predictions and vaccine allocation. Finally, I worked on analyzing the representation power of neural networks and contributing to explain theoretically why neural networks work so well in data-driven prediction.

PhD Papers

Undergraduate Research Projects

  • Head Teaching Assistant, MIT
    15.093/6.255 Optimization Methods, Graduate (Masters, PhDs, MBAn, MBA & others), Fall 2021. (220 students)
  • Teaching Assistant, MIT
    15.093/6.255 Optimization Methods, Graduate (Masters, PhDs, MBAn, MBA & others), Fall 2020. (125 students)
  • Instructor, Mathematical Olympiad
    President of the Moroccan Mathematical Olympiad society. (2016-2019)
  • Instructor, Institut Bossuet
    Instructor in advanced mathematics for undergraduate students of top french classes préparatoire.

    Holistic Robust Data-Driven Decisions
    Upcoming: ORC seminar spring 2023, SIAM Conference on Optimization 2023.
    Past: INFORMS Annual meeting October 2022, MoroccoAI webinar October 2022, ICCOPT July 2022, ORC Student Seminar October 2022.
    Learning and Decision-Making with Data: Optimal Formulations and Phase Transitions
    Past: ORC Student Seminar October 2021; INFORMS annual meeting October 2021 (see video).
    Minimal Representation Learning: Toward more Interpretable and Efficient Offline Reinforcement Learning
    Past: INFORMS annual meeting November 2020; ORC Student Seminar April 2021 (see video); MSOM Conference June 2021; INFORMS Healthcare Conference July 21st 2021 ; INFORMS annual meeting October 2021.
    The Representation Power of Neural Networks
    Past: MIT SIAM student seminar December 2020 (see video); ORC Student Seminar March 2021; Poster session ICLR 2022.