About Me

I am a graduate student currently studying Computer Science at Georgia Institute of Technology. Over the years, I’ve had the privilege of working alongside talented engineers who have helped shape my approach to programming, design, and product thinking. I’m particularly driven by projects that blend strong engineering with real-world impact.

Previously, I worked on the Model Development Group at Experian, where I deployed over 60 Python models to a proprietary platform that calculated custom credit scores and adverse action codes for clients looking to manage lending risk. I contributed across the full development lifecycle: using Python and AWS SageMaker for model development, Docker for containerization, and AWS S3 and CloudWatch for deployment. These models processed populations of over 300 million records in real time.

Beyond building, I also maintained and supported these systems—debugging 20+ monthly real-time failures and restoring usability at double the previous response rate. I advised clients on model architecture and deployment strategy, and mentored peers on the Experian Ascend platform, which hosts over 400 credit scoring models.

Outside of work and academia, I enjoy reading and learning about new things. I find it interesting to research linguistics, history, sports, film, and many other aspects of the human experience. As a programmer, I find it important to explore worlds outside the screen we typically live in, to really understand the problems us programmers seek to solve, and how our work relates to these other fields. It is especially rewarding when I can directly apply my understanding of these disciplines toward my software skillset. My interest in film led to the development of a U-net deep learning model that interpolated standard frame rate footage into slow motion video by generating new frames. My interest in sports led to the development of a multiclass XGBoost model that predicts NBA player and game results.

At the end of the day, I hold the belief that all software serves to solve problems and make human lives better. Whether it’s through better data, smarter infrastructure, thoughtful design, or appreciation for the problems at hand, I aim to build programs and tools that reflect