Skip to main content
Return to top

Kyle Felker

Headshot of Kyle Felker
Program Years:
2014–2018
University:
Princeton University
Field of Study:
Applied and Computational Mathematics
Advisor:
James Stone
Degree(s):
Ph.D. Applied and Computational Mathematics, Princeton University, 2019
M.A. Applied and Computational Mathematics, Princeton University, 2015
B.S. Mathematics, and B.A. Physics, The University of Chicago, 2013

Practicum Experience(s)

Princeton Plasma Physics Laboratory (2016)

Practicum Supervisor(s):
William
Tang
Practicum Title:
Machine Learning Applications to Predictive Studies of Disruptions in Tokamaks

Current Status

Status:
Assistant Computational Scientist
Research Area:
Applied and Computational Mathematics
Personal URL:
https://www.anl.gov/profile/kyle-gerard-felker

Annual Program Review Abstracts

Fellow Presentation
: Computational Efficiency of High-order Finite Volume Methods for Magnetohydrodynamics (
2018
)
Fellow Poster
: Fourth-order Accurate Magnetohydrodynamics Calculations in Athena++ (
2017
)
Fellow Poster
: High-order Finite Volume Methods in ATHENA++ (
2016
)
Fellow Poster
: Numerical Methods for General Relativistic Radiative Transfer (
2015
)