Research

My research focuses on understanding and optimizing customer behavior in digital marketplaces.

I recently completed a PhD in Operations Management at McGill University, where I designed and executed a randomized field experiment to understand how different types of promotions impact customer behavior over time. I used heterogeneous treatment effect analysis and reinforcement learning to personalize promotional strategies based on customer engagement and long-term value.

Key areas of interest:

• Promotion framing and customer psychology
• Multi-agent reinforcement learning for marketing optimization
• Causal inference in digital experiments
• Customer lifetime value modeling
• Subscription and platform business analytics

Notable methodologies:

• Randomized controlled trials (RCT)
• Mixed-integer linear programming (MILP)
• Q-learning and explainable RL
• A/B testing and heterogeneous treatment effect modeling