<![if !vml]><![endif]>Connor Wagaman
[mylastname] [at] bu.edu
I am a first-year PhD student in computer science at Boston University, where I am advised by professors Adam Smith and Marco Gaboardi. I am interested in data privacy (e.g., differential privacy), and in issues of privacy and security more generally.
I graduated in May 2022 with an AB and SM (advanced standing) in computer science from Harvard University, where I did research in differential privacy with Professor Salil Vadhan.
Authors are in alphabetical order, as is common in some areas of computer science.
<![if !supportLists]>• <![endif]>Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It.
Sílvia Casacuberta, Michael Shoemate, Salil Vadhan, Connor Wagaman.
Presented at ACM CCS 2022 and TPDP 2022 (selected for a spotlight talk).
<![if !supportLists]>• <![endif]>Finite-Precision Arithmetic Isn’t Real: The Impact of Finite Data Types on Efforts to Fulfill Differential Privacy on Computers.
Senior thesis, Harvard University (highest honors). Advised by Professor Salil Vadhan.
<![if !supportLists]>• <![endif]>Harvard CS 208 – Applied Privacy for Data Science: Spring 2022.
<![if !supportLists]>• <![endif]>Harvard CS 20 – Discrete Mathematics for Computer Science: Spring 2021, Spring 2020.