Dae Woong (David) Ham

I conduct research in the intersection of causal inference and business/social science applications. A lot of my research is motivated by an existing problem in real practice, e.g., the need for modern large digital tech companies to efficiently analyze hundreds of thousands of experiments with proper statistical guarantees, without a feasible or appropriate existing solution. Though I am in the operations department, I have obtained my Ph.D. from the Harvard Statistics Department and plan to continue to do methodological work in statistics. 

I have worked closely with tech companies, e.g. Netflix, on experimentation and causal inference problems. On the other hand, I have also worked on social science problems with interesting statistical gaps in the current literature. Finally, I have written papers just purely on causal inference methodologies and theory, contributing to the growing literature and importance of causal inference methods in practice. 

At a high level, I am a causal inference researcher. Specifically, I am interested in experimentation, adaptive and sequential inference, Difference-in-Difference and Matching, randomization inference (Fisher-Based Testing), design-based causal inference, and non-parameteric statistics.