My research currently explores differential privacy as well as its connections to machine learning, economics, and algorithmic game theory. In general, I'm interested in ideal strategic behavior, actual behavior, and the gap between the two.
Prior to USC, I completed my undergraduate studies at
Virginia Tech in 2015,
where I earned my B.S. in Computer Science, B.S. in Mathematics, B.A. in Economics, and B.S. in Statistics.
At VT, I was an undergrad research assistant under T. M. Murali, where I explored hypergraph algorithms and their applications to biological networks. Here, I was the primary designer and implementer of halp, the hypergraph algorithms package.
Brendan Avent, Aleksandra Korolova, David Zeber, Torgeir Hovden, Benjamin Livshits
26th USENIX Security Symposium. 2017. [link] [arxiv]
Selected for presentation in Private and Secure Machine Learning Workshop @ICML. 2017.
Selected for presentation in 3rd Workshop on the Theory and Practice of Differential Privacy @CCS. 2017.
Anna Ritz, Brendan Avent, T. M. Murali
ACM/IEEE Transactions on Computational Biology and Bioinformatics. 2015. [link]
Brendan Avent, Anna Ritz, T. M. Murali
VTURCS Research Symposium. Poster. 2015. [pdf]
Brendan Avent, Nicholas Sharp, Dhruv Batra
SIAM Annual Meeting. Undergrad Presentation. 2014.
In the Spring of 2015, I TA-ed VT's Stat 4106: Theoretical Statistics II with Bill Woodall and also CS/Stat 4654: Intermediate Data Analytics & Machine Learning with Byron Smith.