444 Hopper Hall
SD486C: Computational Finance
SI342: Theory of Computing
I came to the US Naval Academy after over 25 years in the Financial Industry, where I worked on algorithms and strategies to better understand financial markets and extract actionable information. Over the years, the work evolved from linear regressions to applying more novel and esoteric approaches, such as AI, Machine Learning, and NLP.
Hint: If you are looking for a Capstone project/independent research/Trident and are interested in learning more about how markets work, let's talk!
My research still circles these topics. Financial markets are profoundly complex and intertwined, and there is no "one size fits all" approach to understanding them and ultimately profiting from them. But there are some good news. Ideas from Machine Learning lend themselves naturally to quantifying, interpreting, and ultimately better understanding complex topical domains, such as financial markets, by sifting through heterogeneous input data, including time series, text, and beyond.
I hold a Ph.D. in Computer Science from Columbia University in New York (1993) and the CFA designation (Chartered Financial Analyst) from the CFA Institute (2001).