My primary research interest spans two interrelated areas, Optimization and Data Analytics. I believe these are tools that can be applied to various domains to improve the efficiency of systems and processes. While my dissertation research is primarily focused on Operations Research with application in airline industry, my professional work experience is related to Optimization and Data Analytics using statistical methods.
One dimension of my research is around Supply Chain Management and Revenue Management with a focus on quantitative optimization solution. My dissertation work concerns modeling and optimization techniques on Choice-based Revenue Management (RM), an area that is crucial to today’s air travel industry. We applied a multinomial logit (MNL) choice model to capture the demand dependencies, and proposed a computational efficient heuristic, named Choice-Based EMSR, which is scalable and perfect for real-time application.
The other area of my research lies in the area of Data Analytics using statistical methods. At Sabre, I work on several projects that focus on statistical methods. One involves demand estimation using time series models with large airline travel data sets, another applies Classification and Regression Tree (CART) based statistical model to predict passenger behavior in airline travel using PNR (Passenger-Name-Record) data.