Boston Headshot

About Me

Hi! My name is James and I'm a medical student at Harvard-MIT who enjoys ballroom dancing, edge casing, and armchair philosophizing. I wanted to document my learning, projects, and interests throughout my education, and this is where I've decided to put it.

A not-so-brief bio:

Hometown   House Logo

I grew up in Sugar Land, Texas, a suburban outgrowth of Houston. It was a fantastic place to grow up, especially with Houston's diverse communities and food scene. I spent most of high school with the speech and debate team, where I first started learning about public policy and value ethics. I spent the rest of my time volunteering and working at the Texas Medical Center, before coming to the Northeast for college.

Undergrad   Graduation Cap Logo

I graduated from Yale, where I studied Statistics and Biochemistry. My coursework inspired me to explore computational research in molecular diagnostics, which led me to Gerstein Lab at Yale and Zak Lab at Harvard. Outside of class and lab, I spent most of my time learning and practicing ballroom dance, which has been my favorite hobby for more than five years.

Med School  Stethoscope Logo

Now at Harvard, I joined a subgroup of medical students dual-enrolled at MIT. The HST program brought me together with an amazing community of aspiring clinicians and researchers, all with the same unabashed love of science and wholehearted sense of mission. Learning and growing with them has been such an incredible adventure—they've taught me so much.

ML Startup   ANN Logo
HST's curriculum also gave me a lot of freedom to pursue my research interests in unconventional ways. In my first year, I had the remarkable opportunity to join the tech startup PathAI and its vision to bring computer vision to pathologist workflows. As part of the machine learning team, I worked on deep learning for tissue and cell prediction, as well as survival models for human-interpretable risk stratification.

All of these experiences have gotten me really excited about the possibilities for modern computational methods applied to age-old clinical problems. Specifically, I was blown away by research that described superhuman diagnostic classifiers for diabetic retinopathy, skin cancers, and heart arrhythmias. It's an incredible feat, and I love how this kind of work has a direct and powerful link to improving care. One day, if all goes well, I would love to get involved in and contribute to similar advances.