I’m a quantitative researcher working at the intersection of systematic trading and machine learning. Most recently I spent three years at Chicago Trading Company, where I developed trading signals and contributed to portfolio construction for the firm’s volatility arbitrage strategy. Before that, I was a senior researcher at the Voleon Group, a hedge fund in the Bay Area with ML-based investment strategies.

I received my PhD in statistics in 2018 from the Wharton Statistics Department at the University of Pennsylvania, and my B.S. in mathematics and economics from the University of Chicago in 2010. My published research from grad school focused on understanding tree-based ensemble methods, with various projects in deep learning and applied optimization. You can find my work on Google Scholar. Before graduate school I spent a few years working in the macroeconomic policy group of the Federal Reserve Bank of Chicago.

I’m currently on garden leave. During this time I’ll be teaching a course on machine learning at the University of Chicago and thinking a lot more about agentic research workflows and the statistical foundations of transformers.

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