Connor Wagaman

[mylastname] [at] bu.edu

I am a 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 with an AB and SM (advanced standing) in computer science from Harvard University, where I did research in differential privacy with Professor Salil Vadhan.

Research

Authors are listed alphabetically.

• Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation.

Palak Jain, Adam Smith, Connor Wagaman.

Presented at Oakland (IEEE S&P), May 2024.

• 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).

• Finite-Precision Arithmetic Isn’t Real: The Impact of Finite Data Types on Efforts to Fulfill Differential Privacy on Computers.

Connor Wagaman.

Senior thesis, Harvard University (highest honors). Advised by Professor Salil Vadhan.

News

• March 2024. I will give a talk on “Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation” (joint work with Palak Jain and Adam Smith) at Northeastern’s Theory Seminar.

• March 2024. I gave a talk on “Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation” (joint work with Palak Jain and Adam Smith) at Boston University’s Theory Seminar.

• September 2023. I presented a poster for “Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation” (joint work with Palak Jain and Adam Smith) at TPDP 2023.

• August 2023. Sílvia Casacuberta, Isaac Robinson, and I gave a talk on “Augmenting Fairness with Welfare: A Framework for Algorithmic Justice” at Harvard’s Bridging Privacy working group.

• June 2023. “Augmenting Fairness with Welfare: A Framework for Algorithmic Justice” (joint work with Sílvia Casacuberta and Isaac Robinson) appeared at the 2023 European Workshop on Algorithmic Fairness. Sílvia and Isaac gave an in-depth talk on it.

• May 2023. I was named a Hariri Institute graduate student fellow. Thank you to Boston University’s Hariri Institute for the fellowship, and to the BU computer science department for the nomination!

• April 2023. Sílvia Casacuberta and I gave a talk at Northeastern University’s NDS2 seminar on our paper, “Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It” (co-authored with Michael Shoemate and Salil Vadhan).

Teaching assistantships

• Boston University CS 330 – Introduction to Analysis of Algorithms: Fall 2023.

• Harvard CS 208 – Applied Privacy for Data Science: Spring 2022.

• Harvard CS 20 – Discrete Mathematics for Computer Science: Spring 2021, Spring 2020.