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.
Typical collaborations include:
Similarity-Sensitive Entropy: Induced Kernels and Data-Processing Inequalities (arXiv:2601.03064).
Technical notes and case studies, including: