Ali Aouad
Associate Professor Management Science and Operations
BSc MSc (Ecole Polytechnique) PhD (Massachusetts Institute of Technology)
Dr Ali Aouad's research revolves around the design and analysis of algorithms, with applications to operations management. He is broadly interested in choice modelling, revenue management and matching platforms. His work ranges from analyzing the fundamental properties of algorithms to driving their implementation in the practice.
He holds a PhD in Operations Research from Massachusetts Institute of Technology (MIT) and an MS and BS in Applied Mathematics from Ecole Polytechnique (Paris). He has research articles published in Management Science, Operations Research, Mathematics of Operations Research and Mathematical Programming. Dr Aouad was awarded the Best Student Paper Prize by the Operations Research Center at MIT in 2015, and was a finalist in the INFORMS Nicholson Prize competition in 2016.
Alongside academia, Dr Aouad has worked and consulted for various technology firms. Before joining LBS, he spent a year at Uber’s Marketplace Data Science (San Francisco), where he contributed to the design and implementation of new algorithms that improved the efficiency of the matching platform.
- Personal website
- aaouad@london.edu
- +44 (0)20 7000 8858
- Choice Modelling
- Inventory and Revenue Management
- Matching Platforms
- Approximation Algorithms
- Stochastic Optimization
2023
Market segmentation trees
Aouad A; Elmachtoub A; Johnson Ferreira K; McNellis R
Manufacturing & Service Operations Management 2023 Vol 25:2 p 648-667
The stability of MNL-based demand under dynamic customer substitution and its algorithmic implications
Aouad A; Segev D
Operations Research 2023 Vol 71:4 p 1216-1249
2022
Dynamic Stochastic Matching Under Limited Time
Aouad A; Saritac O
Operations Research 2022 Vol 70:4 p 2349-2383
Online assortment optimization for two-sided matching platforms
Aouad A; Saban D
Operations Research 2022 Vol 69:4 p 2069-2087
Technical Note - An Approximate Dynamic Programming Approach to The Incremental Knapsack Problem
Aouad A; Segev D
Operations Research 2022 Vol 71:4 p 1414-1433
The exponomial choice model for assortment optimization: an alternative to the MNL model?
Aouad A; Feldman J; Segev D
Management Science 2022 Vol 69:5 p 2814-2832
2021
Assortment optimization under consider-then-choose choice models
Aouad A; Farias V; Levi R
Management Science 2021 Vol 67:6 p 3368-3386
2020
Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences
Aouad A; Segev D
Management Science 2020 Vol 67:6 p 3519-3550
Dynamic stochastic matching under limited time
Aouad A; Saritac O
Proceedings of the 21st ACM Conference on Economics and Computation; July 2020; 789-790
2019
Approximation algorithms for dynamic assortment optimization models
Aouad A; Levi R; Segev D
Mathematics of Operations Research 2019 Vol 44:2 p 487-511
The ordered k-median problem: surrogate models and approximation algorithms
Aouad A; Segev D
Mathematical Programming 2019 Vol 177:1-2 p 55-83
2018
Greedy-like algorithms for dynamic assortment planning under multinomial logit preferences
Aouad A; Levi R; Segev D
Operations Research 2018 Vol 66:5 p 1321-1345
The approximability of assortment optimization under ranking preferences
Aouad A; Farias V; Levi R; Segev D
Operations Research 2018 Vol 66:6 p 1661-1669
2021
The Pandora's Box Problem with Sequential Inspections
Aouad A; Ji J; Shaposhnik Y
Social Sciences Research Network
2020
An Approximate Dynamic Programming Approach to The Incremental Knapsack Problem
Aouad A; Segev D
ARXIV
Online assortment optimization for two-sided matching platforms
Aouad A; Saban D
Social Sciences Research Network
2019
Assortment optimization under consider-then-choose choice models
Aouad A; Farias V F; Levi R
Social Sciences Research Network
Click-based MNL: algorithmic frameworks for modeling click data in assortment optimization
Aouad A; Feldman J; Segev D; Zhang D
Social Sciences Research Network
The exponomial choice model: algorithmic frameworks for assortment optimization and data-driven estimation case studies
Aouad A; Feldman J; Segev D
Social Sciences Research Network
The Stability of MNL-Based Demand under Dynamic Customer Substitution and its Algorithmic Implications
Aouad A; Segev D
Social Sciences Research Network
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Emerging Topics in MSO II
Emerging Topics in MSO II
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Emerging Topics in MSO II