I am currently a software engineer at the Johns Hopkins Applied Physics Lab. I have a PhD in Computer Science and Masters in mathematics from Brown University, and a bachelors degree in the same two fields from the University of Notre Dame. I was also a research scientist at Meta, where I studied how to scale training and inference of neural networks used in their mobile ads pipeline. Though I don't publish much these days, some of my prior work is available on Google scholar and DBLP.
My expertise in and zeal for mathematics has long been a driving force in my career, though today I find that I am most passionate about bridging theory and practice by building systems that apply state-of-the-art research. To that end, I enjoy working with reseachers across a variety of domains, and developing scalable software solutions that make their vision a reality.
I've served in various roles during the course of my career, including as technical lead on software projects, as principal investigator on research projects, and as an individual contributor doing software development, training machine learning models, and performing data analysis. Recent application domains include cybersecurity, homomorphic encryption, and tracking disinformation in social media.
I am a lifelong learner and am not afraid to tackle problems in unfamiliar domains and pick up new technologies along the way. Some of my latest professional work and technical competencies are described on my LinkedIn profile. I often write about things that I tinker with or read about in my free time on Mastodon, and I used to be more active on Math SE when I did more math during my academic career.
Outside of work, my hobbies include hiking, traveling, being involved with puzzle hunts (having been on Team Providence since 2015), playing board games, and reading. I also listen to a lot of music (particularly indie rock), go to the occasional concert, and like transcribing music by ear.