Hello! I began my PhD in Computer Science in the Fall of 2017. My advisor is Peter Chin, leader of the LISP Group. Before that, I received my BS from Case Western Reserve University in Mathematics.
In between, I worked in data analytics consulting with Mu Sigma, Inc. and as a GRE and SAT instructor for Kaplan Test Prep.
My main research interests lie in machine learning. Within that area, I am interested in time series, optimization, and the application of information theory. Additionally, I am interested in exploring how we can apply machine learning and concepts of sparsity to better understand the brain.
This semester I am taking Randomness in Computing with Sofya Raskhodnikova and Convex Optimization Algorithms with Alina Ene and Lorenzo Orecchia. Previously I took Advanced Algorithms with Steven Homer and Adaptive Data Analysis with Adam Smith. The latter is an exciting topic for me, uniting several of my interests under a single umbrella.
Chin, Sang Peter, Jonathon Cohen, Alison Albin, Mykola Hayvanovych, Elizabeth Reilly, Gavin Brown, and Jacob Harer. "A Mathematical Analysis of Network Controllability Through Driver Nodes." IEEE Transactions on Computational Social Systems 4, no. 2 (2017): 40:51.
Miao, Jiayuan, Gavin Brown, and Philip Taylor. "Theoretically guided design of efficient polymer dielectrics." Journal of Applied Physics 115.9 (2014): 094104.