The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering
Shangdi Yu, Jessica Shi, Jamison Meindl, David Eisenstat, Xiaoen Ju, Sasan Tavakkol, Laxman Dhulipala, Jakub Łącki, Vahab Mirrokni, and Julian Shun
VLDB 2025 (International Conference on Very Large Data Bases)
[pdf]
Parallel algorithms for hierarchical nucleus decomposition
Jessica Shi, Laxman Dhulipala, and Julian Shun
SIGMOD 2024 (ACM Symposium on Principles of Database Systems)
[pdf]
Efficient algorithms for parallel bi-core decomposition
Yihao Huang, Claire Wang, Jessica Shi, and Julian Shun
APoCS 2023 (SIAM Symposium on Algorithmic Principles of Computer Systems)
[pdf]
Hierarchical agglomerative graph clustering in poly-logarithmic depth
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirrokni, and Jessica Shi
NeurIPS 2022 (Conference on Neural Information Processing Systems)
[pdf]
Differential privacy from locally adjustable graph algorithms: k-core decomposition, low outdegree ordering, and densest subgraphs
Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Shangdi Yu, and Julian Shun
FOCS 2022 (IEEE Symposium on Foundations of Computer Science)
[pdf]
Parallel five-cycle counting algorithms
Jessica Shi, Louisa Ruixue Huang, and Julian Shun
JEA 2022 (ACM Journal of Experimental Algorithmics)
Special Issue of SEA 2021
[pdf]
Parallel batch-dynamic k-core decomposition
Quanquan C. Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun
SPAA 2022 (ACM Symposium on Parallelism in Algorithms and Architectures)
Best Paper Award
[pdf]
Theoretically and practically efficient parallel nucleus decomposition
Jessica Shi, Laxman Dhulipala, and Julian Shun
VLDB 2022 (International Conference on Very Large Data Bases)
[pdf] [slides] [video]
Scalable community detection via parallel correlation clustering
Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Łącki, and Vahab Mirrokni
VLDB 2021 (International Conference on Very Large Data Bases)
[pdf] [slides] [video]
Hierarchical agglomerative graph clustering in nearly-linear time
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirrokni, and Jessica Shi
ICML 2021 (International Conference on Machine Learning)
[pdf]
Parallel clique counting and peeling algorithms
Jessica Shi, Laxman Dhulipala, and Julian Shun
ACDA 2021 (SIAM Conference on Applied and Computational Discrete Algorithms)
Best Student Presentation
[pdf] [slides] [video]
Parallel five-cycle counting algorithms
Louisa Ruixue Huang, Jessica Shi, and Julian Shun
SEA 2021 (International Symposium on Experimental Algorithms)
Invited to Special Issue
[pdf] [slides]
The Graph Based Benchmark Suite (GBBS)
Laxman Dhulipala, Jessica Shi, Tom Tseng, Guy Blelloch, and Julian Shun
GRADES-NDA 2020 (Graph Data Management Experiences and Systems and Network Data Analytics)
[pdf]
Parallel algorithms for butterfly computations
Jessica Shi and Julian Shun
APoCS 2020 (SIAM Symposium on Algorithmic Principles of Computer Systems)
Published in Massive Graph Analytics [book]
[pdf] [slides]
Exponential bounds on graph enumerations from vertex incremental characterizations
Jérémie Lumbroso and Jessica Shi
ANALCO 2018 (Meeting on Analytic Algorithmics and Combinatorics)
[pdf] [slides]
Thesis: Bridging theory and practice in parallel clustering
Jessica Shi (Advisor: Julian Shun)
[pdf] [slides]
Thesis Proposal: Bridging theory and practice in parallel clustering
Jessica Shi (Advisor: Julian Shun)
[pdf]
Undergraduate Thesis: Dominating sets in graphs with no long induced paths
Jessica Shi (Advisor: Maria Chudnovsky)
[pdf] [slides]
Parallel maximal independent set algorithms for graphs and hypergraphs (survey)
Zeyuan Shang, Jessica Shi, and Yiqiu Wang
[pdf]
Rational secret sharing under fairness frameworks
Jessica Shi and Evan Wildenhain
[pdf] [slides]
On the undecidability of the Magnus, word, isomorphism, and Markov property problems for finitely presented groups (survey)
Jessica Shi (Advisor: Adam Levine)
[pdf]
