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 research lies at the intersection of computational consumer modeling and machine learning, with a focus on understanding how consumers evaluate and choose among complex, experience-based products. I study settings such as music, fragrances, and digital platforms, exploring how consumers experience, interpret, and respond to products that are often subjective, sensory, or difficult to describe. Methodologically, I develop quantitative models, including Bayesian nonparametric approaches and deep generative frameworks, to analyze high-dimensional data, including text, networks, and product features, with the goal of uncovering the latent structure of consumer preferences and improving data-driven decision-making. I teach MBA courses in Marketing Management and Marketing Analytics.

I studied at Louis-le-Grand (Paris, France) with a focus on mathematics and physics, and hold an engineering degree in applied mathematics, statistics, and economics from ENSAE Paris . I also received an M.Sc. and a Ph.D. from Columbia Business School .

Research

Published & Forthcoming Journal Articles

Modeling Dynamic Consumer Preferences from Few-shot Data: A Meta-Learning Approach
Mingzhang Yin, Khaled Boughanmi, and Anirban Mukherjee (2026) [Watch Video Overview]
Journal of Marketing Research, forthcoming.
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) [Watch Video Overview]
Journal of Marketing Research, 2021.
- Lead article.
Randomized Algorithms for Lexicographic Inference
Rajeev Kohli, Khaled Boughanmi, and Vikram Kohli (2019) [Watch Video Overview]
Operations Research, 2019.

Working Papers

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.
A Bayesian Latent-Factor Framework for Causal Decomposition in High-Dimensional Experiments
Khaled Boughanmi, Raghuram Iyengar, and Young-Hoon Park [Watch Video Overview]
Meaningful Differentiation in Markets with Overlapping Categories: Evidence from Fragrances
Khaled Boughanmi and Kamel Jedidi [Watch Video Overview]

Work in Progress

Modeling Graph Treatment Selection: A GCN-Based Framework for Causal Inference
Khaled Boughanmi, Mingzhang Yin, and Sachin Gupta
- AIM 2025 Conference Awards, Finalist.
The Impact of Experiential Store on Customer Purchases
Khaled Boughanmi, Raghuram Iyengar, and Young-Hoon Park