NSF-Funded Project (2022 - 2024): I worked as a researcher on a project funded by the National Science Foundation (NSF) where I was responsible for implementing mathematical models from research papers using RStan and related BUGS/JAGS languages. My tasks included profiling and designing algorithms for knot selection and other spatiotemporal sampling methods.
NEON Summer Internship (2023): During a 10-week summer internship at NEON (National Ecological Observatory Network), I developed software for both back and front ends to track samples as they were collected and shipped to labs for processing.
Research Interests: My research is centered around improving how we interact with and make sense of large datasets, particularly through AI techniques such as natural language processing (NLP) and deep neural networks. I am interested in creating systems that enable efficient data aggregation and analysis, and I aim to drive advancements in AI that dramatically enhance human productivity and address the growing complexity of data in the modern world.