Research

Here is a list of my publications:

Conference Publications:

Online k-means Clustering on Arbitrary Data Streams (ALT 2023).
TLDR: Designed online clustering algorithms with order-optimal error which select poly(log n, k) centers.

Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model (CCS 2022).
TLDR: Proposed novel one-round subgraph counting algorithms in the shuffle model of differential privacy.

Balancing Utility and Scalability in Metric Differential Privacy (UAI 2022). Source Code
TLDR: Used linear programming to optimize an algorithm for privately releasing text.

Communication-Efficient Triangle Counting under Local Differential Privacy (USENIX 2022).
TLDR: Dramatically reduced communication complexity for private triangle counting protocols proposed in previous work.

Locally Differentially Private Analysis of Graph Statistics (USENIX 2021).
TLDR: Proposed novel two-round private graph algorithm for counting triangles in graphs; it obtains significantly reduced error over one-round protocols.

Capacity-Bounded Differential Privacy (NeurIPS 2019).
TLDR: Defined differential privacy when adversary capacity is limited. Proved stronger privacy guarantees against such adversaries.

Preprints

Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees
TLDR: Considered Hierarachical Clustering under differential privacy (it’s hard) and proposed a better algorithm in the stochastic block model.

Robustness of Locally Differentially Private Graph Analysis Against Poisoning
Source Code
TLDR: Used randomized response to protect private degree estimation algorithms against malicious parties who send poisoned data.

Other Publications

Privacy Amplification Via Bernoulli Sampling (TPDP workshop at ICML 2021).
TLDR: Investigated privacy amplification of mechanisms which sample from Bernoulli distributions given a private parameter.