About

I am a software engineer working on backend and distributed systems, with a background in large-scale data infrastructure.

Most recently I was a Software Engineer at Dyneti Technologies, where I built an end-to-end asynchronous fraud-detection workflow for a credit-card scanning mobile SDK — moving ML inference off the synchronous scan path cut scan-to-response latency by over 75%. Before that I built TerraPrecise, a Python/FastAPI weather-risk data platform on AWS, designing its storage layer across PostgreSQL/PostGIS, TimescaleDB, and S3 by access pattern, and a containerized microservice architecture isolating GPU inference from the lightweight API and alerting services in front of it.

I came to software engineering from research. I completed my Ph.D. at the University of Virginia, where I spent six years writing parallel Python pipelines over 100+ TB of satellite and model data to study large-scale atmospheric dynamics. That is where I learned that most of the interesting problems are systems problems — and it is why I tend to reach for questions about data layout, failure modes, and where the boundaries between services should go.

I am currently finishing an M.S. in Computer Science at Georgia Tech (December 2026) and looking for software engineering roles.

Elsewhere: Projects · CV · GitHub · LinkedIn

_{My doctoral research was in climate science, advised by Prof. Kevin Grise, and produced peer-reviewed work on jet stream variability and cloud–circulation interactions. Publications, research summaries, and my academic CV are archived here.}