I am interested in exploring patterns and structure in complex systems—whether social, linguistic, biological, or computational. Since mathematics is the study of structures and patterns, it’s generally the best tool for describing those systems (and also has aesthetic value as its own discipline).

I have a B.S. in Mathematics and minors in Linguistics, Computer Science, and Formal Logic.

Most of my on-the-job training has come while working under software engineers, computer science professors, and statisticians. This has led to my proficiency with object-oriented programming in C++, Python, and Java; data manipulation and analysis in R and PostgreSQL; and machine learning techniques with PyTorch, scikit-learn, and OpenNMT. My areas of academic research have included phonetic transliterations of historical English surnames, applications of large-scale language models (e.g. GPT-2) to procedural generation of NPC dialogue in video games, experimenting with procedural music generation (both MIDI and audio), and studying the effects of tagging information about language families on encoder-decoder multilingual neural machine translation models.

Most recently, I have been working at Pacific Northwest National Laboratory on two different projects. The first project has involved data and software engineering for a framework of graph analytic pattern-matching algorithms (i.e., subgraph isomorphism methods) for anomalous pattern-of-life detection. I have played a variety of roles on the project, assisting with data curation, building an ETL pipeline, and front-end visualization. For the second, I have been leveraging LLMs and clustering algorithms to improve graph-based models of threat patterns in cyber-physical systems.