Peilin Zhong
Peilin Zhong is a research scientist at Google NYC in the Algorithms and Optimization team lead by Vahab Mirrokni. He received his Ph.D. from Columbia University (Under supervision of Alex Andoni, Cliff Stein, and Mihalis Yannakakis). Previously, he was an undergraduate student at Institute for Interdisciplinary Information Sciences (Yao Class), Tsinghua University. He has broad interests in theoretical computer science, mainly in design and analysis of algorithms. Some particular interests include parallel and massively parallel algorithms, private algorithms, sketching, streaming algorithms, graph algorithms, machine learning, high dimensional geometry, metric embedding, numerical linear algebra, clustering, and other algorithms related to large-scale data computation.
Authored Publications
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Google
Measuring Re-identification Risk
Travis Dick
Adel Javanmard
Josh Karlin
Gabriel Henrique Nunes
SIGMOD (2023)
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Advances in Neural Information Processing Systems (2022)
Stars: Tera-Scale Graph Building for Clustering and Learning
Warren Schudy
NeurIPS 2022 (2022)
Near-Optimal Private and Scalable k-Clustering
Shyam Narayanan
NeurIPS 2022 (2022)
