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David Eisenstat

David Eisenstat

David is a software engineer in the Large-Scale Optimization team. He earned a PhD in Computer Science from Brown University in 2014.

Research Areas

Algorithms and Theory

Authored Publications

Google

Design and analysis of bipartite experiments under a linear exposure-response model

Christopher Harshaw

Fredrik Savje

David Eisenstat

Vahab Mirrokni

Jean Pouget-Abadie

Proceedings of the 23rd ACM Conference on Economics and Computation (2022), pp. 606

ParHAC: Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth

David Eisenstat

Jessica Shi

Jakub Łącki

Laxman Dhulipala

Vahab Mirrokni

NeurIPS'22 (2022)

Scalable Community Detection via Parallel CorrelationClustering [Scalable Data Science]

David Eisenstat

Jessica Shi

Jakub Łącki

Laxman Dhulipala

Vahab Mirrokni

VLDB 2021

Hierarchical Agglomerative Clustering on Graphs in Nearly Linear Time

David Eisenstat

Jessica Shi

Jakub Łącki

Laxman Dhulipala

Vahab Mirrokni

ICML'21 (2021)

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