Experience
Master's of Computer Science (ML focus) at Georgia Institute of Technology
2025-2027. Atlanta, GA
I will pursue a Master's degree in Computer Science in the Fall of 2025 at Georgia Institute of Technology. Very excited to have been accepted to one of the top institutes in the country!
Relevant Coursework: Software Development Process, Artifical Inteligence, Natural Language Processing, Deep Learning, Data Analytics and Security, Visual Analytics, Analytics Modeling, Machine Learning for Trading
Bachelor of Sciences in Statistics (Machine Learning Track) at University of California, Davis (GPA: 3.9/4.0)
2021-2024. Davis, CA
In December, I graduated with Honors two quarters early. Relevant coursework that bolstered my skills as a Statistician/Data Scientist/ Machine Learning Engineer included: Vector Analysis, Applied Linear Algebra, Regression Analysis, Probability Theory, Statistical Data Science, Data Structures and Algorithms, Time Series Analysis, Non-parametric Statistics, Statistical Data Technologies, Machine Learning, Bayesian Statistical Inference, Unsupervised Learning, Computer Vision, Analysis of Categorical Data and a Data Science Capstone course, to name a few.
Stealth AI Startup, Artificial Intelligence Engineer.
2024-2025. San Francisco, California
This startup is building an AI-powered, proximity based social app that is focused on connecting people who would have otherwise never met each other.
As an Artificial Intelligence Engineer on the software development team, I created proprietary algorithms that improved profile matching efficiency. The startup is still in stealth mode, so I can't reveal much more at the moment. Sign up here to be notified as soon as the app launches.
Naval Research Laboratory, Machine Learning Engineer
2024. Washington, DC
The Naval Research Laboratory (NRL) is a center for scientific and technological innovations aimed towards the improvement of the U.S. Navy and Marine Corps.
While here, I worked on the development of custom network policies and reward structures for the training of autonomous high altitude aerostats - unmanned vehicles that utilize reinforcement learning to reach target areas via wind flows. I also developed methods to produce large volumes of realistic synthetic wind data that was used for training the agents when real-world data became too sparse. We submitted out findings to the 2025 IEEE Aerospace Conference, and the manuscript can be found here.
UC Davis Stats Department, Data Analyst
2023-2024. Davis, CA
While studying at the university, here, I was privileged to contribute to the statistics department by way of creating a data analysis tool for a browser extension powered by Chrome API. The extension automated LinkedIn parsing for hundreds of UC Davis Alumni, tracking key analytics like career trajectories and higher education pathways. Sadly, this project is defunct as a result of LinkedIn adding strict anti-scraping mechanisms to their site.
