I am a Computer Systems Engineer in the Center for Computational Sciences and Engineering (CCSE) in the Computing Sciences Area at Lawrence Berkeley National Laboratory
I received my Doctorate in Applied and Computational Mathematics from the University of South Carolina in 2019. My dissertation involved the development and analysis of a model for polymer gel behavior using stochastic partial differential equations that leveraged parallel computation at scale to gain insight into the microstructure behavior behind macro-level fluid characteristics. As part of this work, I developed and optimized code for Nvidia GPUs in C with Cuda to efficiently simulate the behavior of close to 1 million individual links in the gel network. To manage simulations and analyze the large amount of data produced, I created tools and workflows in Bash, MATLAB, Python and R.
Outside of my dissertation work, I participated in scientific endeavors and spent a significant amount of time teaching mathematics. As an NSF Mathematical Sciences Graduate Intern at the Lawrence Berkeley Lab, I created visualizations for unit tests and profiled the exascale multiphase fluid code MFiX-Exa. I also took part in industry focused activities such as the Graduate Student Mathematical Modeling Camp and the Mathematical Problems in Industry workshop. As an instructor, I taught several mathematics courses ranging from college algebra to differential equations across California State University East Bay and the University of South Carolina.
In addition to my broad interests in mathematical models, simulation and scientific computing, my experiences as an English tutor and teacher, have given me have a passion for improving technical documentation and clear communication.
For additional information please see the CCSE website.