I am currently a Visiting Assistant Professor at Amherst College. In 2018, I received my Ph.D. in mathematics under the supervision of Sergi Elizalde at Dartmouth College. I was previously a postdoc at Wake Forest University. My research is in discrete applied probability and the mathematical foundations of data science.

I enjoy thinking about questions including:

- How can we understand the community structure of data? What is the meaning of
*local*? What do we mean by*clusters*? - Suppose that, rather than numeric distances, we only have
*distance comparisons*(among triples of points). How can we effectively leverage that limited information? What kind of structure is required for interpretability? - Can we articulate measures of the degree of
*unpredictability*of a process given that we can only witness a single (relatively short) sequence of outcomes?

Language families revealed from cognate information and the PaLD algorithm. The algorithm provides interpretable edge-weights and threshold for distinguishing between strong and weak ties. No additional inputs/parameters (beyond distance information), distributional assumptions, optimization criteria nor iterative proceedures are employed.