I'm a software engineer and a neuroengineering researcher, and I've been doing both long enough that they've started to influence each other. At JPMorgan I build Python pipelines for market risk reconciliation across 40+ source systems, batch processing frameworks, and reporting tooling for risk teams. I finished my MS at Johns Hopkins last spring with a 4.0, neuroengineering concentration.

The research started at Cornell's DAIL Lab, where I spent four years on EEG data cleaning, signal processing pipelines, and reviewing papers on BCI and neuroarchitecture. Slow work, but it's how you learn what's actually hard before you start building your own things.

Since then I have been building fluency in the parts of the stack that actually matter: signal processing, classical ML, deep learning on time series, and the boring infrastructure that lets you run an experiment a hundred times and still trust the results. The problems I want to work on sit at the intersection of engineering and biology. I want to build things that actually ship.

This June I'm attending CNEW in Munich, a selective global neurotech entrepreneurship workshop sponsored by Blackrock Neurotech and run on Stanford Biodesign methodology. After that I'm looking for a software engineering role in NYC where the domain actually matters: healthcare AI, biomedical systems, or early-stage engineering with real ownership.