Summary
George Chadderdon is a cognitive modeler and experienced AI/ML engineer with over two decades of interdisciplinary work spanning computational neuroscience, pattern recognition, and production software development. He builds well-documented, modular systems—from ACT-R and Common Lisp cognitive agents to Python-based web frameworks and Flask/Vue.js full‑stack applications—bridging research-grade models and deployable tools. His career includes patented sensor-based stress detection, SBIR-winning proposals, and contributions to public‑health optimization tools that improved high-performance batch simulation and front-end migrations. Comfortable from low-level C/C++ signal processing to modern Python data stacks and Dockerized deployments, he pairs deep mathematical training with practical engineering. He has academic credentials culminating in a PhD in Psychology and Cognitive Science and a track record of presenting, publishing, and securing grants and patents that translate theory into applied systems. An uncommon strength is translating natural-language instructions into finite-state/knowledge-graph task representations to enable instruction-based learning in synthetic teammates.
10 years of coding experience
17 years of employment as a software developer
University of California, San Diego
Ph.D., Psychology and Cognitive Science, Ph.D., Psychology and Cognitive Science at Indiana University Bloomington
B.S., Computer Engineering, B.S., Computer Engineering at University of Illinois Urbana-Champaign
High School, High School at Illinois Mathematics and Science Academy