Hello! I'm Owen, a computer science Ph.D. student and Knight-Hennessy Scholar at Stanford, advised by James Zou. I study how we can AI can help us solve big scientific problems.
Some of the things I'm interested in right now:
I did my undergrad at the University of Tennessee, Knoxville, and I previously worked with Marinka Zitnik at Harvard Medical School as a research associate.
I've had the pleasure of working on using AI to do cool science in diverse domains, from designing new polymer materials to nominating new targets for multiple sclerosis to predicting geographic coordinates of poplar trees just from their genomes.
Updates
Selected work
arXiv preprint · 2026
ReasonOps is an annotation-free method that segments chain-of-thought traces into 7 recurring reasoning operators—discourse-level moves such as backtracking, inferring, and hypothesizing—that generalize across model families and benchmarks, enabling model identification, correctness estimation, and early quality assessment before a trace completes.
Neural Information Processing Systems (NeurIPS) · 2025
bioRxiv · 2025
ProCyon is an 11B-parameter model that predicts and generates protein phenotypes across molecular and therapeutic scales, enabling transfer to poorly characterized proteins.
Neural Information Processing Systems (NeurIPS) · 2023
TimeX learns interpretable surrogate masks that mirror predictor behavior through a novel consistency loss, delivering faithful explanations for time-series models.
