Amine Bennouna

Kellogg School of Management
Northwestern University

Contact: amine.bennouna [at] kellogg.northwestern [dot] edu
CV, Google Scholar, LinkedIn


Hello! I am an Assistant Professor in Operations at the Kellogg School of Management, Northwestern University. Prior to that, I spent one year as a postdoctoral researcher at the MIT Laboratory for Information & Decision Systems (LIDS), working with Prof. Asuman Ozdaglar and Prof. Saurabh Amin.

I completed my PhD at the MIT Operations Research Center in 2024, advised by Prof. Bart Van Parys. Prior to joining MIT, I graduated from Ecole Polytechnique in 2019 majoring in Applied Mathematics.


headshot

My research focuses on understanding how machines, or artificial intelligence (AI), learn to make decisions. Specifically, I work on developing novel learning algorithms to enable efficient, data-driven decision-making while emphasizing key reliability attributes. Enhancing these learning algorithms has significant practical implications, driven by the rapid adoption of AI, and is based on fascinating mathematical models. My research involves theoretical and algorithmic advancements, leveraging tools from probability theory, optimization, and geometry.
Keywords include: Data-driven Decision-making, Experimentation, Data Value, Stochastic Optimization, Distributionally Robust Optimization, Human-AI Interaction.

Recent News
  • INFORMS 2025: I will be chairing a session and giving a talk on the value of data in decision-making and optimization.
    • Co-chairing with Lin Fan the session "Experimentation and Decision-making" featuring Omar Bennouna (MIT), Prof Omar Besbes (Columbia), Tiffany Cai (Columbia), and Prof Yassir Jedra (Imperial) (Mon Oct 27, 2:45pm, B202).
    • Presenting "Data Informativeness in Decision-Making" in Yeganeh Alimohammadi's Modern AI and Marketplaces session (Sun Oct 26, 1:15pm, B315).
    • My co-author Omar Bennouna will present our joint paper at the Data Mining and Decision Analytics Workshop on Saturday as a Best Paper finalist.
  • Our paper What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization was accepted in NeurIPS 2025! It is also finalist of the INFORMS Data Mining and Data Analytics Workshop Best Paper Award (Theoretical Track).
  • Upcoming Panel: I will be part of a panel discussion at the TTIC Workshop Incentives for Collaborative Learning and Data Sharing, on August 15th.
Papers
  • Robust Two-Stage Optimization with Covariate Data
    with Bart Van Parys & Julien Pinede.
Teaching
  • Optimization Methods, MIT 15.093/6.255 | Head Teaching Assistant
    Graduate (Masters, PhDs, MBAn, MBA), Fall 2021. (180 students)
  • Optimization Methods, MIT 15.093/6.255 | Teaching Assistant
    Graduate (Masters, PhDs, MBAn, MBA), Fall 2020. (120 students)
  • The Analytics Edge, MIT 15.071 | Guest Lecturer
    Graduate (MBA), Fall 2023. (80 students)
  • The Advanced Analytics Edge, MIT 15.072 | Guest Lecturer
    Graduate (MBAn), Fall 2023. (100 students)
  • Classes Préparatoires Instructor (Louis-le-Grand, Saint Louis, Henri IV)
    Instructor and examiner in advanced mathematics for undergraduate students of top French classes préparatoires
Service
    Reviewer
    Operations Research, Management Science, Annals of Applied Probability, NeurIPS, Automatica, INFORMS Journal on Optimization.
Talks
The background is a typical geometric motif of Moroccan mosaic tilework. These beautiful geometric patterns, found everywhere in Morocco, date back to the 10th century. Beyond their beauty, they are facinating mathematical objects. (Credit: Zellij gallery)