I focus on the intersection of math, industrial data, and software systems. I spent my time at LSU (2020–2024) bridging Data Science and Mathematics to understand the mechanics behind neural networks, rather than just treating them as "black boxes."

I am responsible for the end-to-end machine learning lifecycle, which includes building robust ingestion logic for industrial data, designing and evaluating models for specific user needs, and developing the backend logic to deliver real-time inference.

I take the lead on the mathematical and neural network components of our systems, but I work as a collaborative part of the development team. My focus is on ensuring that the intelligence I build follows established best practices, integrates cleanly with our broader platform, and remains stable in production environments. I am currently focused on researching more resilient infrastructure solutions to ensure our deployments scale alongside the data.