Summary
James Scully is a computational-neuroscience PhD candidate and research assistant with eight years of experience translating chaotic neural dynamics into practical ML and GPU-accelerated tools. He combines rigorous dynamical-systems theory with hands-on engineering—shipping full-stack AI apps and graph-neural models that decode olfactory patterns—while publishing on chaos, locomotion, and adaptive coordination. At Georgia State he models central pattern generators to inform multi-agent and agentic decision systems, turning theoretical insights into algorithms that predict, classify, and control real-world behavior. Fluent in Python, Julia, and CUDA, he bridges first-principles reasoning and production-ready code to extract signal from messy data. Uncommonly, his background spans both founding startups and running a small service business, giving him practical product and operational sensibilities alongside deep technical expertise.
8 years of coding experience
6 years of employment as a software developer
California Polytechnic State University, San Luis Obispo
High School, High School at Decatur High School
Doctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at Georgia State University