Christina G. Taylor

Key Interests: High Performance Computing, Numerical Methods for PDEs, Function Approximation, Engineering

My research interests are in the intersection of mathematics, computer science/scientific computing, and engineering. 

Each of these three fields, while powerful in their own right, cannot reach their full potential for meaningful impact without the others. My interest in both academia and industry is in bridging the gaps between these fields by participating in, promoting, and improving interdisciplinary research and collaboration.

For my CV and/or resume, please see my LinkedIn page.

Currently Projects:

• Paper: "A Sequential Function Approximation Algorithm for Training Radial Basis Function Neural Networks." Joint work with Dr. Andrew Meade and Dr. Katelyn Jarvis at NASA Ames.  Based on thesis work by Graham Smith (2020) and Arti Qormemeti (2018).

• Paper: "Energy stable state redistribution cut-cell discontinuous Galerkin methods for wave propagation." Thesis work with my advisor, Dr. Jesse Chan, and Dr. Lucas Wilcox at the Naval Postgraduate School Department of Applied Mathematics.

• Ph.D. proposal preparation. 

Past Highlights:

• Oral Presentation at SIAM (Society for Industrial and Applied Mathematics) Computational Science and Engineering 2023 Conference in Amsterdam, NED. March 2023.

• Instructor of record, CMOR 421/521: High Performance Computing (prev. CAAM 420/520). Department of Computational Applied Mathematics and OR, Rice University, Spring 2023.

• Simula Summer School in Computational Physiology in Oslo, NOR and San Diego, CA. Summer 2022.

• Alumni of Argonne National Lab's Training Program in Extreme Scale Computing. Summer 2021.

• Graduate Intern with the Numerical Algorithms Group at BP's Center for High Performance Computing. Summers of 2020 and 2021.

• Intern at University of Florida's Center for Compressible Multiphase Turbulence. Summer 2018.

• Engineering Practicuum Intern at Google. Summers of 2016 and 2017.