Summary
James Wade is a research scientist and analytical chemist with 13 years of experience specializing in materials characterization, chemometrics, and data-driven materials design at Dow. He blends hands-on polymer analytics with statistical analysis, machine learning, and data visualization to accelerate characterization workflows and enable AI-ready materials science. At Dow he led Citizen Data Science training, built internal R-based tools and packages to scale lab automation, and helped define enterprise AI strategy and standards. His work includes a 10x faster polyethylene characterization method and applied deep learning/Bayesian modeling to product performance. Trained as a PhD chemist with a background in silicon photonic biosensors and microfluidics, he uniquely translates precision-measurement techniques from academia into industrial-scale solutions. Based in Michigan, he focuses on sustainable materials and practical AI adoption to make recycling and polymer performance more robust.
13 years of coding experience
2 years of employment as a software developer
University of Illinois Urbana-Champaign
Bachelor of Science, Chemistry, Summa Cum Laude, Bachelor of Science, Chemistry, Summa Cum Laude at Furman University