Kyle Felker

Kyle Felker is a Researcher at Argonne National Laboratory in the Computational Science Division, where he applies deep learning techniques to fusion energy science as part of the Aurora Early Science Program. He is also a member of the Catalyst team at Argonne.

His educational background includes:

• Ph.D. in Applied and Computational Mathematics from Princeton University
• B.A. in Physics from the University of Chicago

Kyle's research interests span:

• Deep learning and artificial intelligence
• Fusion energy sciences
• Computational astrophysics
• High-performance computing
• Numerical analysis
• Reproducibility in computational science
• Performance portability

He was honored as a Department of Energy Computational Science Graduate Fellow (CSGF) from 2014 to 2018.

Kyle is actively engaged in Argonne's research ecosystem, particularly through his work in the Leadership Computing Facility (postdoctoral experience) and the Catalyst team.