Marissa Masden

I blend mathematical theory from a range of fields including topology, geometry, combinatorics and algebra, to approach foundational questions about the behavior and properties of neural network functions. My dissertation uses algebraic constructions from oriented matroid theory, geometric ideas from piecewise linear Morse theory, and fundamental constructions from algebraic topology. I write code, mostly in Python (Pytorch) and Sage, to obtain experimental and empirical measurements of the objects I study. My background and research experiences additionally include applications of graph theory and topology in computational chemistry, materials science, and computer vision. I am interested in finding new applications of computational topology in the mathematical and natural sciences, and enjoy working on interdisciplinary projects.