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.