Software Engineer (CARSR)
B.S. in Cognitive Science (neuroscience/AI concentrations) and Computer Science
Software engineer with a dual background in Cognitive Science (neuroscience/AI concentrations) and Computer Science, and 2+ years building, debugging, and modernizing robust C++ and Python systems in a demanding production environment (FAA). Strengths in data pipelines, automation, and turning messy, multi-source real-world data into reliable analysis. Now looking to move into research-adjacent software engineering that builds the tools and data infrastructure scientists and researchers rely on.
A multi-agent orchestration experiment: three LLM agents collaborate on a task, then propose and vote on structured changes to their own coordination protocol between rounds. The scaffolding stays fixed and every change is an explicit, logged proposal. A study in bounded, auditable iteration and agent coordination. Built with Gemini 2.5 Flash, structured output via Pydantic, and no agent frameworks.
Projects from my undergraduate years, kept as a record of early explorations in ML and systems programming.
A Python machine learning project using custom recurrent neural networks to predict future stock prices. Trained on 5200 days of IBM closing prices from the AlphaVantage API. Demonstrates time series prediction with detailed mathematical analysis of the underlying calculus.
A C++ project demonstrating third-party library integration with TCLAP for command line argument processing. The program reads text files, performs case conversion based on arguments, and writes results to output files. Showcases C++ file I/O, library integration, and shell scripting.