My research focuses on developing statistical methods and frameworks that help Marketers, Clinicians, and Policy-makers better conduct Randomized Controlled Trials (A/B testing) and also optimally target subjects and treatments in a budget-constrained, heterogeneous treatment effect environment. These questions fall in the line of literature related to Heterogeneous Treatment effects and Multi-Armed Bandits. I use a mix of Statistics, Machine Learning, and Causal Inference to solve the above problems.


In Progress