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.
- NowCofounder & Chief Scientific Officer, HEARTio
- DoctoratePh.D. in Bioengineering, University of Pittsburgh (2024)
- UndergraduateChemical Engineering & Biochemistry, Villanova University (2016)
- Based inPittsburgh, PA
I studied chemical engineering and biochemistry at Villanova, then came to Pittsburgh in 2016 for a Ph.D. in Bioengineering. Two years in, while I was still a graduate student, I cofounded HEARTio with Utkars Jain and Michael Leasure. I have been doing both kinds of work ever since: building models of cells in the lab, and building models of the heart's electrical signal at HEARTio.
The two have more in common than they look. Both start with noisy, incomplete data, and both end with a prediction that someone has to decide whether to trust. Most of what I care about lives in that last step: what a model's numbers actually mean for the person on the other end of them.
HEARTio
HEARTio's goal is to identify patients with coronary artery disease more quickly, more accurately, and at a fraction of the cost of the current standard of care. Our product, ECGio, 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.
As Chief Scientific Officer I lead the science: study design, model development and validation, regulatory strategy, and our publications. Along the way ECGio earned FDA Breakthrough Device Designation, we published validation studies in the Canadian Journal of Cardiology and JACC: Advances, and we were issued three U.S. patents. In 2026 we closed a $4.25 million seed round to run the pivotal study for our FDA submission and joined Innovation Works' AlphaLab Health portfolio. The full story, from a 90-second pitch in 2018 to first-place finishes at Baylor, Tulane, and LiftOff PGH, is on the news and publications page.
Building a diagnostic for a living means thinking constantly about sensitivity, specificity, and who actually gets tested. I wrote up how I explain those ideas, with a chest-pain triage simulator you can play with, in Diagnostic accuracy: from the confusion matrix to the cath lab.
Research
I earned my Ph.D. in 2024 in the MeLoDy Lab, advised by Dr. Natasa Miskov-Zivanov. My dissertation, Automated and Manual Assembly of Computational Models for Biological Systems: Applications to Macrophage Activation and CAR-T Cells, followed two threads: accurately simulating how macrophages respond to specific stimuli, and automating the assembly and extension of biological models from published literature. The second thread became my first-author paper in IEEE/ACM Transactions on Computational Biology and Bioinformatics. The same modeling work produced the mathematical model behind a Nature Communications paper on SNAP-CAR receptors with Jason Lohmueller's lab.
A prototype of the macrophage signaling network, which I built during my thesis as a proof of concept, 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.
Elsewhere
I am on LinkedIn, GitHub, Google Scholar, and Instagram.