Hi, I'm Bern. I graduated from the University of Chicago in June 2026 with a B.A. in Economics with honors, specializing in data science, and a B.S. in Computer Science, specializing in machine learning. I am an incoming research assistant at the Federal Reserve Bank of Chicago.
My work spans econometrics, quantitative research, and systems programming. My senior thesis asks whether a language model can read a job interview and predict worker retention better than human recruiters. It extends work I began as a research assistant at Chicago Booth, where I built NLP pipelines over the same transcript data. This past summer I conducted quantitative research at a startup in Vienna, building covariance forecasting engines and the system that tested them inside a factor allocation strategy.
On the systems side, I've implemented virtual memory and a file system for an x86 kernel, a relational storage engine in Rust, and an LZW compressor in C. I have also built a data pipeline at Red Ventures that gave a $21M revenue channel its first centralized view of variable costs.