Maya Wallach is a Physics PhD student and graduate research assistant at Michigan State University with seven years of research experience applying machine learning and computational methods to experimental particle physics and fluid dynamics. She has built Faster R-CNN and DCGAN pipelines to identify and generate muon-track training data for Fermilab’s Modern Modular Bubble Chamber and has simulated k-L turbulence and Rayleigh–Taylor instabilities during a Los Alamos internship. Comfortable coding in Python and C, Maya blends hands-on model development with domain knowledge in detector physics and unsupervised track classification, work that has been presented at the Division of Nuclear Physics. Based in the Detroit metro area, she brings a rare mix of applied ML, simulation expertise, and experimental instrumentation experience to physics-driven software problems.
6 years of coding experience
4 years of employment as a software developer
Stafford Senior High School
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Michigan State University
Contributions:5 releases, 71 pushes, 1 branch in 1 year 5 months
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