I am a medical student at Washington University in Saint Louis School of Medicine. My research applies statistical and computational approaches to surgery, and to medicine at large.
I graduated from Johns Hopkins University with a BS in Computer Science in May 2019 and an MSE in Applied Mathematics & Statistics in December 2019. While there I was fortunate to be advised by Suchi Saria and Avanti Athreya. During my gap year I worked as an Assistant Research Engineer at my alma mater. I was a part of the NeuroData lab where I worked with Carey Priebe on statistical graph inference and with Joshua Vogelstein on causal inference from observational health data.
I started medical school at WashU in 2021. In 2024, I took a research year during which I was the CNS AI fellow at NYU's OLAB under Dr. Eric Oermann, co-advised by Dr. Eric Leuthardt at WashU. During that time I trained the first neurosurgical chatbot that can view imaging — CNS-Obsidian — which was evaluated in a real-world randomized trial.
During that time I also contributed to Daniel Alber's Nature Medicine study showing that medical language models are vulnerable to data-poisoning attacks. I also supervised student work on how we evaluate medical AI, including Krithik Vishwanath's Nature Medicine paper demonstrating that generalist models like GPT, Claude, and Gemini outperform dedicated clinical tools like OpenEvidence on real-world queries.
My work spans clinical artificial intelligence, computational safety, and connectome statistics. I also often think deeply about, but never had time to do formal work in, quantum mechanics and computing, consciousness, and causality.
Selected papers below.