
Alessandro Epasto
I am a senior staff research scientist at Google, New York working as Tech Lead of a privacy team in the Google Research Algorithms and Optimization group led by Vahab Mirrokni.
I received a Ph.D in computer science from Sapienza University of Rome, where I was advised by Professor Alessandro Panconesi and supported by the Google Europe Ph.D. Fellowship in Algorithms, 2011.
I was also a post-doc at the department of computer science of Brown University in Providence (RI), USA where I was advised by Professor Eli Upfal.
During my Ph.D. studies I was twice an intern at Google Mountain View (2012, 2014) and once at Google NYC (2013).
My research interests include algorithmic problems in machine learning and data mining, in particular in the areas of privacy, clustering, and large scale graphs analysis.
Authored Publications
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Scalable Private Partition Selection via Adaptive Weighting
Justin Y. Chen
Forty-second International Conference on Machine Learning (2025)
Private estimation algorithms for stochastic block models and mixture models
Hongjie Chen
Tommaso D'Orsi
Jacob Imola
David Steurer
Stefan Tiegel
54rd Annual ACM Symposium on Theory of Computing (STOC'23) (2023)
Measuring Re-identification Risk
Travis Dick
Adel Javanmard
Josh Karlin
Gabriel Henrique Nunes
SIGMOD (2023)
Near-Optimal Private and Scalable k-Clustering
Shyam Narayanan
NeurIPS 2022 (2022)
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Advances in Neural Information Processing Systems (2022)
Scalable Differentially Private Clustering via Hierarchically Separated Trees
Chris Schwiegelshohn
David Saulpic
2022 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2022) (to appear)
Fair Hierarchical Clustering
Benjamin Moseley
Marina Knittel
Yuyan Wang
Neurips 2020
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Vaggos Chatziafratis
AISTATS, AISTATS, AISTATS (2020), AISTATS (to appear)
Fair Correlation clustering
23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020) (2020) (to appear)