Diana Chua Halikias
Welcome! I am a third year math PhD Student at Cornell University. My advisor is Alex Townsend.
I study numerical analysis and am especially interested in randomized linear algebra, matrix theory, PDEs, and PDE learning theory.
I completed my undergraduate degree in math at Yale.
My CV is here. You can email me at dh736 at cornell dot edu.
Elliptic PDE learning is provably data-efficient
with Nicolas Boulle and Alex Townsend, preprint. (arxiv).
Structured matrix recovery from matrix-vector products
with Alex Townsend, preprint. (arxiv).
Arbitrary depth universal approximation theorems for operator neural networks
with Annan Yu, Chloé Becquey, Matthew Mallory and Alex Townsend, preprint. (arxiv)
Discrete variants of Brunn-Minkowski type inequalities
with Bo'az Klartag and Boaz Slomka, Ann. Fac. Sci. Toulouse Math. (6), Vol. 30, no. 2, (2021), 267-279. (journal, arxiv).
A Cheeger inequality for graphs based on a
with Ed Gelernt, Charlie Kenney, and Nicholas Marshall, Involve 13 no. 3, (2020) 475-486 (journal, arxiv).
I run a Little Math Circle for children in grades K-5 in the Ithaca area.
I mentored a research project on the theoretical aspects of machine learning as part of the 2021 Cornell REU.
I have mentored two directed reading projects with Cornell undergraduates on spectral graph theory.
I am the trivia host at Cornell's graduate weekly trivia night at the Big Red Barn!
I also love rock climbing and playing piano.
At Yale, I worked for three years in the Numismatics department of the Yale University Art Gallery.