I'm a fifth year PhD student at Carnegie Mellon University in computer
science theory, who is very
fortunate to be advised by Gary Miller.
My interests include spectral graph theory and the mathematics behind
machine learning.
Previously, I received my Bachelors from MIT with a degree in mathematics.
Publications
- Functions that Preserve Manhattan Distances
Timothy Chu, Gary Miller, Shyam Narayanan, Mark Sellke
Preprint [arXiv] .
- Algorithms and Hardness for Linear Algebra on Geometric Graphs
Josh Alman, Timothy Chu, Aaron Schild, Zhao Song
FOCS 2020 [arXiv].
- Cheeger and Buser Inequalities for Probability Density Functions,
with Inspired by Machine Learning
Timothy Chu, Gary Miller, Noel
Walkington, Alex Wang
Preprint [arXiv].
- Exact Computation of a Manifold metric, via Lipschitz Embeddings
Timothy Chu, Gary Miller, Donald Sheehy
SODA 2020 [arXiv].
- Graph Sparsification, Spectral Sketches, and Faster Resistance
Computation, via Short Cycle Decomposition
Timothy Chu, Yu Gao, Richard Peng,
Sushant
Sachdeva, Saurabh
Sawlani, Junxing
Wang
FOCS 2018 [arXiv].
Invited to the SICOMP Special Issue.
- Constant Arboricity Spectral Sparsifiers
Timothy Chu, Michael Cohen, Jakub Pachocki, Richard Peng
Preprint [arXiv].
Teaching