Rachel Morris

Currently, I am a Postdoctoral Fellow at Concordia University in the Mathematics and Statistics department, working with Jason Bramburger and Simone Brugiapaglia. 

I received my PhD from NC State in July 2025, under the direction of Ryan Murray. 

For research, I am broadly interested in the mathematical foundations of data science. One direction of my research applies techniques from geometric measure theory and calculus of variations in order to study data-motivated optimization problems. More specifically, I study properties of adversarially robust Bayes classifiers, which arise from image classification problems. More recently, I have been interested in applying compressed techniques to achieve theoretical convergence guarantees for neural network eigenfunction approximation techniques in dynamical systems. This work addresses the reliability of the empirically successful neural network Koopman eigenfunction approximations. 

I am also passionate about teaching and creating an interactive, supportive, and inclusive learning environment for all students. I participated in NC State's "Preparing the Professoriate" professional development program as part of the 2023-2024 cohort. 

Contact me at: rachel (dot) morris (at) mail (dot) concordia (dot) ca 

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