Summary
Daniel Shea is a Head of Artificial Intelligence with a PhD in materials engineering and a decade of experience applying machine learning to mathematical physics, materials science, and healthcare. He leads medical AI development at Prahsys, consults on AI software for the Gates Foundation, and founded an agentic AI platform as CEO of Infinite Monkey Collective, blending research depth with product and business leadership. His background spans end-to-end work from lab-based experiments and device fabrication to scalable Python ML pipelines and production modeling for battery and renewable-energy clients. Notable research includes physics-informed deep learning for nonlinear boundary value problems and dimensionality-reduction approaches for molecular simulations, and he holds a patent from automated organ-on-chip fabrication. Comfortable moving between hands-on engineering, academic publication, and strategic AI direction, he often translates complex physical models into practical predictive systems that have helped secure multimillion-dollar funding. Based in Seattle, he brings a rare mix of experimental, computational, and entrepreneurial experience to AI-driven healthcare and physical sciences problems.
10 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy (PhD) Materials Engineering, Doctor of Philosophy (PhD) Materials Engineering at University of Washington
B.S. Chemical Engineering, B.S. Chemical Engineering at Northeastern University