I'm a math-minded machine learning enthusiast, with a bent toward applications in healthcare. I'm passionate about algorithms that make a difference; if you have an idea about how to improve patient care with data, let's talk.
My current research focuses on temporal data drift, its impact on clinical prediction models, and methods for mitigating model performance degradation over time. Other/past research interests include offline reinforcement learning for healthcare applications, AI/ML for psychiatry, and causal inference. I am supported by a Stanford Graduate Fellowship and a National Defense Science and Engineering Graduate (NDSEG) Fellowship. In my spare time, I am an outdoor enthusiast and amateur photographer (the banner above is a photo I took on a recent trip to Yosemite).