Rajan's research revolves around the design of provably good and practical algorithms for optimization under uncertainty. He seeks to find and study from a theoretical lens, models that capture key algorithmic aspects of real-life problems. His current focus is on problems in revenue management and pricing, especially for online platforms. In general, he is interested in classical and pervasive problems such as submodular function maximization as well as application-driven problems such as appointment scheduling in health care services. Rajan received his Ph.D. in Operations Research from MIT and subsequently did a postdoc at Columbia University. He has also previously worked as a quantitative analyst and holds a B.Tech. in Electrical Engineering from IIT Bombay.
Research Expertise and Interest
algorithms, optimization under uncertainty, Revenue Management, pricing, online platforms