I'm Yafee Khan, a Yale undergraduate studying Computer Science and Physics, working across three interlocking disciplines: data science, applied AI, and algorithm design. I work primarily in Python and Rust, and I'm drawn to problems that don't fit neatly into one of these boxes — where a statistical question needs an algorithmic solution, or an AI system needs to be built on a foundation of rigorous data engineering.
On the data science side, my background includes generating and validating datasets, training and evaluating models, and grounding results in careful statistical analysis rather than surface-level metrics. On the applied AI side, I've built agent architectures, simulation systems, and full-stack tools that turn models into working products. And underlying all of it is a deep interest in algorithms and data structures — the kind of low-level, first-principles thinking that makes both the statistics and the systems actually scale.
Beyond the technical side, I'm curious about markets, physics, and the patterns — statistical or otherwise — that show up in both. When I'm not building or learning, you can usually find me playing tennis, watching movies, or overthinking both with the same intensity I bring to a dataset.