Kyle Pietrzyk

Degree: Ph.D. from Stanford University
Research: Multiscale Modeling
Joined LLNL: October, 2023

Research at LLNL: Kyle develops novel multiscale modeling methodologies and automates their implementation using symbolic computing. By doing so, predictive multiscale models can be developed and deployed in an accelerated, accessible, and generalizable fashion. Kyle is particularly interested in how the advantages of symbolic computing can extend multiscale modeling theory to feasibly and rigorously accommodate realistic system complexities. Kyle primarily investigates transport phenomena in systems related to electrochemistry, energy, and geological porous media. By combining symbolic computing with rigorous theory, Kyle looks to push the boundaries of multiscale modeling and provide a unique combination of feasibility and accuracy for simulating complex practical systems.

Bio: Kyle Pietrzyk is a Lawrence Fellow in the Materials Science Division of the Physical and Life Sciences Directorate. He earned a B.S. (2016) and M.S. (2018) in Mechanical Engineering from Santa Clara University, and a Ph.D. (2023) in Energy Resources Engineering from Stanford University. During his Ph.D., he worked with Prof. Ilenia Battiato to automate the development of multiscale models for reactive mass transport in porous media via symbolic computation. He received the Stanford Graduate Fellowship in Science and Engineering in 2018 and the Henry J. Ramey Fellowship Award from the Energy Science and Engineering Department at Stanford University in 2022.