Jakub Łącki

Jakub Łącki

Jakub Łącki is a research scientist working on graph-mining and large-scale optimization teams. He received his PhD from Univeristy of Warsaw in 2015, advised by Piotr Sankowski. Before joining Google he was a postdoctoral researcher at Sapienza University of Rome, working with Stefano Leonardi.

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TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
Jason Lee
Jakub Łącki
Laxman Dhulipala
Vahab Mirrokni
SIGMOD'24 (2023)
Adaptive Massively Parallel Connectivity in Optimal Space
Jara Uitto
Jakub Łącki
Rustam Latypov
Yannic Maus
SPAA'23 (2023)
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)
Simple Label-Correcting Algorithms for Partially-Dynamic Approximate Shortest Paths in Directed Graphs
Adam Karczmarz
Jakub Łącki
SOSA 2020
Walking Randomly, Massively, and Efficiently
Krzysztof Onak
Jakub Łącki
Piotr Sankowski
Slobodan Mitrović
STOC 2020
Parallel Graph Algorithms in Constant Adaptive Rounds: Theory meets Practice
Hossein Esfandiari
Jakub Łącki
Laxman Dhulipala
Soheil Behnezhad
Vahab Mirrokni
Warren J Schudy
VLDB 2020
Massively Parallel Computation via Remote Memory Access
Hossein Esfandiari
Jakub Łącki
Laxman Dhulipala
Soheil Behnezhad
Vahab Mirrokni
Warren Schudy
SPAA 2019
Reliable Hubs for Partially-Dynamic All-Pairs Shortest Paths in Directed Graphs
Adam Karczmarz
Jakub Łącki
ESA 2019
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