Papers in Referred Journals and Conferences
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection
Qinghua Liu, Seunghak Lee, and John Paparrizos
Proceedings of the VLDB Endowment (PVLDB 2025) Journal, Volume 18, pages 4364-4379
Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods
John Paparrizos and Teja Bogireddy
Proceedings of the VLDB Endowment (PVLDB 2025) Journal, Volume 18, pages 4380-4395
Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression
Kaisei Hishida, Chunwei Liu, John Paparrizos and Aaron Elmore
Proceedings of the VLDB Endowment (PVLDB 2025) Journal, Volume 18, pages 4396-4409
BURST: Rendering Clustering Techniques Suitable for Evolving Streams
Apostolos Giannoulidis, Anastasios Gounaris, and John Paparrizos
Proceedings of the VLDB Endowment (PVLDB 2025) Journal, Volume 18, pages 4054-4063
SPARTAN: Data-Adaptive Symbolic Time-Series Approximation
Fan Yang and John Paparrizos
Proceedings of the ACM on Management of Data (PACMMOD) Journal, Volume 3, Issue 3, Article 220, pages 1-30
Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Feature Explanations
Suchit Gupte and John Paparrizos
Proceedings of the ACM on Management of Data (PACMMOD) Journal, Volume 3, Issue 3, Article 232, pages 1-31
A Structured Study of Multivariate Time-Series Distance Measures
Jens d'Hondt, Haojun Li, Fan Yang, Odysseas Papapetrou and John Paparrizos
Proceedings of the ACM on Management of Data (PACMMOD) Journal, Volume 3, Issue 3, Article 121, pages 1-29
Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures
John Paparrizos, Qinghua Liu, Paul Boniol, and Themis Palpanas
2025 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD 2025), pages 1-11
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
Paul Boniol, Ashwin K Krishna, Marine Bruel, Qinghua Liu, Mingyi Huang, Themis Palpanas, Ruey S Tsay, Aaron Elmore, Michael J Franklin, and John Paparrizos
The VLDB Journal (VLDBJ 2025), Volume 34, Issue 3, pages 1-32
A Survey on Time-Series Distance Measures
John Paparrizos, Haojun Li, Fan Yang, Kaize Wu, Jens E d'Hondt and Odysseas Papapetrou
arXiv preprint
AdaEdge: A Dynamic Compression Selection Framework for Resource Constrained Devices
Chunwei Liu, John Paparrizos and Aaron J Elmore
2024 IEEE 40th International Conference on Data Engineering (ICDE 2024), pages 1506-1519
An Interactive Dive into Time-Series Anomaly Detection
Paul Boniol, John Paparrizos and Themis Palpanas
2024 IEEE 40th International Conference on Data Engineering (ICDE 2024)
ADecimo: Model Selection for Time Series Anomaly Detection
Paul Boniol, Emmanouil Sylligardos, John Paparrizos, Panos Trahanias and Themis Palpanas
2024 IEEE 40th International Conference on Data Engineering (ICDE 2024)
Time-Series Anomaly Detection: Overview and New Trends
Qinghua Liu, Paul Boniol, Themis Palpanas and John Paparrizos
Proceedings of the VLDB Endowment (PVLDB 2024) Journal, Volume 17, pages 4229-4232
Fast Adaptive Similarity Search through Variance‑Aware Quantization
John Paparrizos, Ikraduya Edian, Chunwei Liu, Aaron Elmore, and Michael J. Franklin
38th IEEE International Conference on Data Engineering (IEEE ICDE 2022), pages 2969‑2983
VergeDB: A Database for IoT Analytics on Edge Devices
John Paparrizos, Chunwei Liu, Bruno Barbarioli, Johnny Hwang, Ikraduya Edian, Aaron J. Elmore, et al.
11th Conference on Innovative Data Systems Research (CIDR 2021), pages 1-8
Good to the Last Bit: Data‑Driven Encoding with CodecDB
Hao Jiang, Chunwei Liu, John Paparrizos, Andrew Chien, Jihong Ma, and Aaron Elmore
2021 ACM SIGMOD International Conference on Management of Data (ACM SIGMOD 2021), pages 843‑856
SAND: Streaming Subsequence Anomaly Detection
Paul Boniol, John Paparrizos, Themis Palpanas, and Michael Franklin
Proceedings of the VLDB Endowment (PVLDB 2021) Journal, Volume 14, pages 1717‑1729
PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage
Hao Jiang, Chunwei Liu, John Paparrizos, and Aaron J. Elmore
Proceedings of the VLDB Endowment (PVLDB 2020) Journal, Volume 13, pages 925‑938
Fast and Accurate Time-Series Clustering
John Paparrizos and Luis Gravano
ACM Transactions on Database Systems (ACM TODS 2017) Journal, Volume 42, pages 1-49
Screening for Pancreatic Adenocarcinoma using Signals from Web Search Logs
John Paparrizos, Ryen W. White, and Eric Horvitz
Journal of Oncology Practice (JOP 2016), Volume 12, pages 737‑744
The Social Dynamics of Language Chance in Online Networks
Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna Wallach, et al.
International Conference on Social Informatics (SocInfo 2016), pages 41‑57
Detecting Devastating Diseases in Search Logs
John Paparrizos, Ryen W. White, and Eric Horvitz
2016 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD 2016), pages 559‑568
k-Shape: Efficient and Accurate Clustering of Time Series
John Paparrizos and Luis Gravano
2015 ACM SIGMOD International Conference on Management of Data (ACM SIGMOD 2015), pages 1855‑1870