Hudson Smith

I am an Assistant Professor in the Department of Mathematical and Statistical Sciences at Clemson University and a co-lead of the Clemson/MUSC Artificial Intelligence Hub. I develop machine learning methods that incorporate prior knowledge for data-constrained scientific and medical applications.

The synthesis of established domain knowledge with flexible learning-based methods leads to better anomaly detection, improved sample efficiency, and more explainable inference without sacrificing the expressive power of modern data-driven models. See my publications.

I earned a PhD in theoretical atomic physics from The Ohio State University. As a physicist, I learned the value of first-principles reasoning; as a machine learning researcher, I have seen the power of flexible statistical models. That combination shapes how I approach research. See my physics-based visualizations.