Navdeep Sahni’s research focuses on understanding consumers' purchase decisions and the impact of firms' marketing actions. Navdeep’s studies employ various methodologies ranging from econometric analysis to running field experiments to make inferences from data. His PhD dissertation focused on the effect of online sponsored search advertising on consumer decision-making. For this study Navdeep executed a randomized field experiment and used innovative techniques to estimate the impact of repetition and timing of ads on advertisers' returns. To compare counterfactual advertising strategies, he built a memory-based model of learning through multiple ad exposures.

Navdeep joined Stanford GSB in the summer of 2012. He received his PhD from the University of Chicago Booth School of Business in 2012. In 2011 his dissertation thesis won the ISMS Doctoral Dissertation award. He holds an undergraduate degree (B.Tech + M.Tech.) in Mathematics & Computing from Indian Institute of Technology (IIT Delhi) - 2004. Between undergrad and Doctoral studies, Navdeep worked in the industry for three years in business analytics.