Contact: ayoub.foussoul [at] chicagobooth [dot] edu
            
            CV,
            Google Scholar,
            LinkedIn
          
Hello! I am a Principal Researcher at the University of Chicago Booth School of Business, working with Prof. Ozan Candogan. My research lies at the intersection of deep learning and operations, with a focus on large-scale control problems in supply chains and matching markets.
I am particularly interested in designing deep learning policies that are more stable and efficient by leveraging problem structure. This includes exploiting problem symmetries, compact representations of optimal policies, and smoother reparameterizations that are easier for neural networks to learn. I am also interested in the theory of deep learning, particularly the question of generalization of neural decision making policies and its relation to model architecture and training dynamics.
        I received my Ph.D. from the Department of Industrial Engineering and Operations Research (IEOR) at Columbia University, where I was advised by Prof. Vineet Goyal. During my Ph.D., I developed efficient and theoretically grounded approximation algorithms for sequential decision-making under uncertainty in supply chains and matching markets.
Prior to my Ph.D., I earned a Master’s and a Bachelor’s degree in applied mathematics from École Polytechnique in France.