Khaled Boughanmi

Bio

Khaled Boughanmi

Assistant Professor, Johnson School of Management, Cornell University

I am an Assistant Professor at the Johnson Graduate School of Management at Cornell University .

My primary research interests are in data-driven decision-making and machine learning. I develop quantitative models (e.g., Bayesian non-parametrics, deep generative models) with a focus on applications in digital media (e.g., music), personalization, online marketing, and service systems. I teach MBA courses in Marketing Management and Marketing Analytics.

I am a graduate of Louis Le Grand (France) with a major in mathematics and physics and ENSAE Paris (France), École Nationale de la Statistique et de l'Administration Économique, with a major in applied mathematics, statistics and economics. I also received an M.Sc. and a Ph.D. from Columbia Business School .

Research

Published & Forthcoming Journal Articles

Modeling Categorized Consumer Collections with Interlocked Hypergraph Neural Networks
Khaled Boughanmi, Asim Ansari, and Yang Li (2025) [Watch Video Overview]
Journal of Marketing Research, 2025.
Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices
Ryan Dew, Nicolas Padilla, Lan E. Luo, Shin Oblander, Asim Ansari, Khaled Boughanmi, Michael Braun, Fred Feinberg, Jia Liu, Thomas Otter, Longxiu Tian, Yixin Wang, and Mingzhang Yin (2024)
International Journal of Research in Marketing, 2024.
Dynamics of Musical Success: A Machine Learning Approach for Multimedia Data Fusion
Khaled Boughanmi and Asim Ansari (2021) — Lead article. [Watch Video Overview]
Journal of Marketing Research, 2021.
Randomized Algorithms for Lexicographic Inference
Rajeev Kohli, Khaled Boughanmi, and Vikram Kohli (2019) [Watch Video Overview]
Operations Research, 2019.

Working Papers

Modeling Dynamic Consumer Preferences from Few-shot Data: A Meta-Learning Approach
Mingzhang Yin, Khaled Boughanmi, and Anirban Mukherjee [Watch Video Overview]
A Bayesian Latent-Factor Framework for Causal Decomposition in High-Dimensional Experiments
Khaled Boughanmi, Raghuram Iyengar, and Young-Hoon Park [Watch Video Overview]
From Reviews to Actionable Insights: An LLM-Based Approach for Attribute and Feature Extraction
Khaled Boughanmi, Kamel Jedidi, and Nour Jedidi [Watch Video Overview]
- This research was supported by a Cornell Center for Social Sciences grant.
- Featured in Columbia Business School Research in Brief, 2025.

Work in Progress

Weighting Graphs for Causal Inference
Khaled Boughanmi, Mingzhang Yin, and Sachin Gupta
- AIM 2025 Conference Awards, Finalist.
The Role of Typicality in Shaping Perfume Popularity
Khaled Boughanmi and Kamel Jedidi
The Impact of Experiential Store on Customer Purchases
Khaled Boughanmi, Raghuram Iyengar, and Young-Hoon Park