Shane Sawyer

Graduate Research Assistant

University of Tennessee, Knoxville


Shane Sawyer is an early PhD student in Mathematics at the University of Tennessee, Knoxville. He is a Graduate Research Assistant in the mathematics department working under the direction of Dr. Clayton Webster. His research interests include applying numerical analysis to partial differential equations, developing algorithms to compute approximate solutions to PDEs, and investigating the underlying mathematical frameworks to understand the connections between approximation theory and deep neural networks.


  • Numerical Analysis
  • Numerical Solutions to PDEs
  • High Performance Scietific Computing
  • Applied and Computational Mathematics
  • Machine Learning
  • Fluid Dynamics


  • Early PhD Student in Mathematics

    University of Tennessee, Knoxville

  • MEng in Computational Engineering

    University of Tennessee, Chattanooga

  • BSc in Applied Mathematics

    University of Tennessee, Chattanooga




Applied Mathematics

Recent Experience


Graduate Research Assistant

University of Tennessee, Knoxville

Aug 2019 – Present
Research areas of machine learning to investigate mathematical underpinnings.

Graduate Research Assistant

University of Tennessee, JICS

Aug 2017 – Aug 2019
Assisted in group research activities including continued development of a high performance implementation of bioinformatics code and assisting collaboration efforts with campus partners and other academic partners.


Machine Learning

Andrew Ng’s popular introductory course to Machine Learning that provides an overview of the basics of the field.

Heterogeneous Parallel Programming

An introductory online course teaching the fundamentals of parallel programming algorithms and how to implement them on an Nvidia GPU using the CUDA framework.


  • Ayres 209, University of Tennessee, Knoxvilee, TN, 37996, United States