I’m a Ph.D. mathematician and university professor with a background that spans both theoretical and applied mathematics. My undergraduate education was in applied and computational mathematics and in physics. In graduate school and through the first few years of my research career, I specialized in homological algebra and commutative ring theory, focusing on the bridge between modern algebra and geometry and topology. However, my interests have gradually shifted toward more practical domains, where I now work with probability theory, modeling, and machine learning. You can find my early mathematical research on my arXiv page.

I am also the author of the open source textbook “Probability Theory with a View Toward Machine Learning,” and the creator of a brand new open source Python library, SigAlg, for measure-theoretic probability theory. Links to both are in the menu bar.