About me

Engineer by training, entrepreneur by accident, and a firm believer that a good diagnostic should be fast, accurate, and cheap enough that everyone gets one.

HEARTio

I cofounded HEARTio in 2018 with the goal of identifying patients with coronary artery disease more quickly, more accurately, and at a fraction of the cost of the current standard of care. HEARTio is a digital diagnostic company that uses deep learning to "upgrade" one of the most common and least expensive tests in medicine, the 12-lead electrocardiogram, so that it can flag anatomical coronary disease that a human reader cannot see.

Since then we have earned FDA Breakthrough Device Designation, published a 1,600-patient validation study in the Canadian Journal of Cardiology, been issued two U.S. patents, raised a seed round, and won first place at business plan competitions at Baylor, Tulane, and LiftOff PGH. As Chief Scientific Officer I lead the science: study design, model development and validation, regulatory strategy, and our publications. The full story is on the news and publications page.

Research

I earned my Ph.D. in Bioengineering at the University of Pittsburgh in the MeLoDy Lab, advised by Dr. Natasa Miskov-Zivanov. My dissertation, In Silico Modeling of Macrophage Activation and Communication: Manual and Semi-Automated Assembly of Hybrid Models, had two threads: accurately simulating how macrophages respond to specific stimuli, and automating the assembly and extension of biological models from published literature.

The macrophage signaling network from that work is explorable on this site. A paper I presented and co-authored on translating machine-read literature into executable cell signaling models won the MOD 2017 Best Paper Award. My publications from both the lab and HEARTio are on Google Scholar.

Recognition & press

Elsewhere

I am on LinkedIn, GitHub, Google Scholar, X, and Instagram.