Gavin Brown

About

Hello! I am a third-year Computer Science PhD student at Boston University. I am advised by Adam Smith. I received a BS in Mathematics from Case Western Reserve University in 2015. Before starting my PhD, I worked in data analytics consulting with Mu Sigma, Inc. and as a GRE and SAT instructor for Kaplan Test Prep.

Research and Interests

My research interests are in the theory of machine learning and its applications to privacy and security. I'm interested in understanding the limits of differential privacy and in what situations we can learn without memorizing the data.

Teaching

CS 537 - Randomness in Computing (Sofya Raskhodnikova). Graduate Class. Spring 2020. Teaching Fellow.

CS 330 - Introduction to Algorithms (Adam Smith and Dora Erdos). Undergraduate Class. Fall 2019. Teaching Fellow.

CS 542 - Machine Learning (Peter Chin). Graduate Class. Summer 2019, Session I. Teaching Fellow.

CS 112 - Introduction to Computer Science II (Christine Papadakis-Kanaris). Undergraduate Class. Fall 2018. Teaching Fellow.

CS 542 - Machine Learning (Peter Chin). Graduate Class. Spring 2018. Teaching Fellow.

Publications and Presentations

L. Jensen, G. Brown, X. Wang, J. Harer, S. Chin, "Deep learning for Minimal Context Classification of Block-types through Side-Channel Analysis", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4196.

X. Wang, Q. Zhou, J. Harer, G. Brown, S. Qiu, Z. Dou, J. Wang, A. Hinton, C. A. Gonzalez, S. P. Chin. Deep learning-based classification and anomaly detection of side-channel signals. Cyber Sensing. 2018.

S. P. Chin, J. Cohen, A. Albin, M. Hayvanovych, E. Reilly, G. Brown, and J. Harer. "A Mathematical Analysis of Network Controllability Through Driver Nodes." IEEE Transactions on Computational Social Systems 4, no. 2 (2017): 40:51.

J. Miao, G. Brown, and P. Taylor. "Theoretically guided design of efficient polymer dielectrics." Journal of Applied Physics 115.9 (2014): 094104.

My CV (pdf)