I’m a computer scientist and artist with a passion for exploring the intersection of technology and art. I graduated with High Honors from Oberlin College with a degree in Computer Science and a minor in Mathematics, and I’ve spent the last five years as a Software Engineer at Google. I also create digital images using techniques like linear optimization and constraints, and often share the underlying methodology alongside my pieces – you can see my work at madebymath.art.

My background also includes a deep interest in the medical field, sparked by my time as a pre-med student at Oberlin and involvement in the Brandeis Global Youth Summit. I gained hands-on medical experience as a lab assistant at Georgetown University Hospital’s HLA Lab (Organ Donation Compatibility). I also have early-stage startup experience as a software engineering intern at Optoro, working on their reverse logistics systems.

My research

My main research interest is in interpretable AI. As someone that likes provable answers to problems, black-boxes drive me crazy. I have published a thesis trying to tackle a subset of General AI that uses a “white-box” approach. That paper is called General Game Playing as a Bandit-Arms Problem: A Multiagent Monte-Carlo Solution Exploiting Nash Equilibria. It combines methods from Game Theory and Machine Learning to solve non-deterministic games (like chess) using a simulated multi-agent system that I have implemented on GitHub.

I am also passionate about Math Art, and have drawn a lot of my inspiration from Bob Bosch. Many of my artworks have research papers behind them describing the methodology and approach to creating the final images. That art will be posted on madebymath.art.

My career

Optoro:

As an intern at Optoro, and worked on the full stack from front-end landing pages for major retail websites, to iOS applications, to automated cross-service integration testing.

Google:

I started as an Engineering Resident at Google in 2019.

On the Android Build Team, I helped optimize Android smart-sync for every Android dev. I also worked on an ML build-optimization project.

On the Android Mainline Team, I led the Android API-Coverage initiative that touched 800M+ Android devices.

Finally, on the Developer-GenAI team for Android & Chrome Infrastructure, I led research initiatives and implemented an IDE tool for open-source developers to automatically generate unit-tests. I also created data pipelines and datasets to train Google’s internal code-LLMs.