Events Calendar

CS Colloquium: Wanrong Zhang (Harvard) - Enabling Interactivity to Move Differential Privacy Closer to Practice

Speaker: Wanrong Zhang, Harvard University

Talk Title: Enabling Interactivity to Move Differential Privacy Closer to Practice

Series: CS Colloquium

Abstract: With growing concerns about large-scale data collection and surveillance, the development of privacy-preserving tools can help alleviate public fears about the misuse of personal data. The field of differential privacy (DP) offers powerful data analysis tools that provide worst-case privacy guarantees. However, most of the existing tools in the differential privacy literature only apply to static databases with non-interactive analysis, which release query answers in a single shot. In practice, data analysts often need to perform a sequence of adaptive analyses on data arriving online, which raises the need for interactive data analysis. This development poses two major questions: 1. How can we design interactive mechanisms that strike a better trade-off between privacy and accuracy? 2. Can we combine multiple interactive mechanisms as building blocks to create a more complex DP algorithm?

In this talk, I will discuss some of my work that answers these questions. To answer the first question, I have created a wide set of tools for private online decision-making problems. I will present one example problem for handling online databases---differentially private change-point detection. Second, I will show the optimal composition theorems for composing multiple interactive mechanisms. My work is among the first to address this long-standing gap in the understanding of composition for differential privacy. I will conclude the talk with my future directions.


This lecture satisfies requirements for CSCI 591: Research Colloquium

Biography: Wanrong Zhang is an NSF Computing Innovation Fellow in the Theory of Computing group at Harvard John A. Paulson School of Engineering and Applied Sciences. She is also a member of the Harvard Privacy Tools/OpenDP project. Her primary focus is to address new challenges introduced by real-world deployments of differential privacy. Before joining Harvard, she received her Ph.D. from Georgia Institute of Technology. She was selected as a rising star in EECS in 2022 and a rising star in Data Science in 2021. She is a recipient of the Computing Innovation Fellowship from CCC/CRA/NSF.

Host: Jiapeng Zhang

Location: Olin Hall of Engineering (OHE) - 132

Audiences: Everyone Is Invited

Contact: Assistant to CS chair