Summary
D Smith is an Assistant Professor and applied data scientist with a PhD in Physics and a decade of experience turning complex scientific problems into deployable data products. After a career studying theoretical atomic physics and high-performance computing, they transitioned to industry roles where they built and optimized large analytics pipelines, delivering predictive models and a ~50% runtime speedup for healthcare advertising attribution. At Clemson University they moved from Research Associate to Director of Applied Machine Learning and now faculty, blending research rigor with client-facing insights and production-focused engineering. Comfortable across R, ETL, and HPC environments, they excel at translating noisy, multi-source data into actionable decisions and reproducible workflows. An engagement-driven collaborator, D brings both peer-reviewed research pedigree and hands-on pipeline refactoring experience to academic and applied ML problems.
10 years of coding experience
12 years of employment as a software developer
B.S., B.A, Physics, Mathematics, B.S., B.A, Physics, Mathematics at Erskine College
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at The Ohio State University