Bio
R&D Associate Staff at ORNL :: Exploring the intersection of Data Science and Advanced Manufacturing
I research how data science principles may be leveraged for metal AM and other manufacturing process throughout the entire toolchain - modeling and simulations, process optimization, data management, in-situ monitoring, defect detection, and post-build analysis.
Awards
- 2024
- ORNL Inventor Awards. Commercial copyright awarded — ML-Based Stamping Quality Prediction and Optimization
- ORNL Inventor Awards. Four licensing awards — Peregrine
- 2023
- ORNL Inventor Awards. Patent awarded, Seven licensing awards — Peregrine
- 2022
- UT-Battelle Technology Transfer Award. Development and transfer of the AI-based Peregrine software platform with 12 licenses awarded over the past 12 months — Peregrine
- ORNL Inventor Awards. Commercial copyright awarded, Nine licensing awards — Peregrine
- 2021
- ORNL Inventor Awards, 2021. Five licensing awards — Peregrine
- 2020
- UT-Battelle Research Accomplishment Award. Successful fabrication, characterization, certification, and deployment of nickel superalloy turbine blades fabricated via AM — Solar Turbine Project
Education
2024 PhD Data Science and Engineering, University of Tennessee, U.S.
2016 MS Computer Engineering, University of Tennessee, U.S.
2015 MBA Business Administration, University of Tennessee, U.S.
2014 BS Computer Engineering, Clemson University, U.S.
Trademarks and Patents
L. Scime, V. Paquit, D. Goldsby, W. Halsey, C. Joslin, M. Richardson, D. Rose, D. Siddel, “Systems and methods for powder bed additive manufacturing anomaly detection,” US20220134435A1, May 5, 2022. https://patents.google.com/patent/US20220134435A1/en?oq=US20220134435