Many firms regularly introduce new products. Before the launch of any new product, firms need to make various operational decisions, which are guided by the sales forecast. The new product sales forecasting problem is challenging when compared to forecasting sales of existing products. For...

We consider the dynamic pricing problem of a retailer who does not have any information on the underlying demand for a product. The retailer aims to maximize cumulative revenue collected over a finite time horizon by balancing two objectives: \textit{learning} demand and \textit{maximizing}...

Problem definition: We study personalized product recommendations on platforms when customers have unknown preferences. Importantly, customers may disengage when offered poor recommendations.Academic / Practical Relevance: Online platforms often personalize product recommendations using bandit...

One of the greatest challenges of the COVID-19 pandemic has been the way evolving regulation, information and sentiment has driven waves of the disease. Traditional epidemiology models, such as the SIR model, are not equipped to handle these behavioral based changes. We propose a novel multipeak...

Governments use consumer incentives to promote green technologies (e.g., solar panels and electric vehicles). Our goal in this paper is to study how policy adjustments over time will interact with production decisions from the industry. We model the interaction between a government and an...

Problem definition: Online retailers provide recommendations of ancillary services when a customer is making a purchase. Our goal is to predict the Net Present Value (NPV) of these services, estimate the probability of a customer subscribing to each of them depending on what services are offered...