Attending the 2026 International Statistics Symposium

This spring I will be traveling to Kansas City to present a poster at the International Statistics Symposium. It is my first time attending the symposium in person, and I am both excited and a little nervous to gather feedback from a community whose papers have shaped so much of my own thinking over the past three years.

My poster will highlight a two-stage screening procedure that integrates model-free correlation measures with a lightweight refinement step. The first stage sweeps through the full predictor space using a rank-based dependence measure that is robust to heavy tails, and the second stage applies a targeted refinement to the surviving candidates using a small held-out fold. The result is a screening pipeline that keeps the computational cost close to the raw first stage while dramatically reducing the false discovery rate on realistic simulations.

The method is designed for practitioners working with large omics datasets who need a fast, interpretable first pass over their predictor space. In our collaborations with a genomics lab, the same pipeline that used to take several hours on a workstation now runs on a laptop in under ten minutes, which has been transformative for the exploratory phase of their studies.

Beyond the poster, I am looking forward to the invited sessions on causal inference in observational health data and on modern variable selection under dependence. Both areas sit adjacent to my dissertation work, and I have a running list of open questions I would love to discuss with the speakers over coffee.

I am also planning to attend the graduate student mixer on the second evening. Some of the most useful conversations I have had at previous workshops happened well outside any formal session, and I want to make room for that kind of serendipity in my schedule.

If you are attending the symposium, please stop by the poster session on Thursday afternoon. I am always happy to talk about dimension reduction, statistical pedagogy, or the perpetual challenge of choosing the right tuning parameter. And if you know of a great local restaurant in Kansas City, I am very much taking recommendations.