Designing efficient experiments and statistical modeling strategies.
I'm a statistician developing efficient optimal experiment design tools that work for survey sampling, A/B testing, and other data collection challenges. My work blends new frameworks in information theory with applied modeling to quantify uncertainty and make adaptive experiment design practical. I also specialize in tractable probabilistic modeling, enabling efficient probabilistic queries and inference. For marketing teams, I work on marketing mix modeling, incrementality measurement, and experiment design for marketing decisions.
Things I work on:
Similarity-Sensitive Entropy under Representation Change and Inference (arXiv:2601.03064).
Optimal experiment design demos: adaptive A/B testing and active learning for record linkage.
SPN uncertain data explorer: Probabilistic model trained on incomplete data and
queried like a database for mixed, missing, interval/censored, and set-valued observations.
Technical explanations, including: