Ali Aouad's research interests are at the interface of operations, computer science, and economics. His academic work focuses on algorithms and decision processes with applications covering supply and demand management, market design and digital platforms, as well as public and societal operations.
Before MIT, Aouad was an Associate Professor at the London Business School (LBS). Alongside academia, Aouad has worked and consulted for technology firms. In 2017-2018, he was an applied scientist at Uber Technology’s Marketplace (San Francisco), where he developed product innovations related to the platform's matching and pricing systems. Prior work experiences include public sector strategic consulting at the Boston Consulting Group (Paris and Casablanca).
Aouad is an associate editor for Operations Research and Management Science. He holds a PhD in Operations Research from MIT and an MS and BS in Applied Mathematics from Ecole Polytechnique (Paris).
Selected teaching and research awards:
2025 Runner up in the 2025 INFORMS Revenue Management and Pricing Section Impact Prize
Best teacher award LBS masters of management program (2022, 2024) and named one of the 2023 Poets & Quants Best 40-Under-40 MBA Professors.
2024 Winner of 2024 POMS Applied Research Challenge for “Designing Layouts for Sequential Experiences: Application to Cultural Institutions”
2024 Finalist in 2024 POMS Applied Research Challenge for “Food Subsidies and Substitution: Experimental Evidence from Indian Micro Retail Panel Data”
2023 “Food Subsidies and Substitution: Experimental Evidence from Indian Micro Retail Panel Data”: Runner-up in 2023 INFORMS TIMES Best Working Paper Award; Finalist in 2023 INFORMS Public Sector OR Best Paper Award
2023 Selected for funding by the 2022 ERC Starting Grant panel for “Pathway Operations: Theory and Application to Museums” (£1.1M)
2022 2nd prize of INFORMS Junior Faculty Interest Group for: “Representing Random Utility Choice Models using Neural Networks"
2021 Finalist of INFORMS Best OM paper in Operations Research for: “Greedy-like Algorithms for Dynamic Assortment Planning under Multinomial Logit Preferences”
