| 2026 | SIGMOD | GlassboxAD: An Interactive System for Dissecting Hierarchical Time-Series Anomaly Detection. | Mingyi Huang, Qinghua Liu, Paul Boniol, John Paparrizos |
| 2026 | WSDM | A Comprehensive Guide to Time-Series Anomaly Detection. | John Paparrizos, Paul Boniol, Qinghua Liu, Themis Palpanas |
| 2025 | KDD | Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures. | John Paparrizos, Paul Boniol, Qinghua Liu, Themis Palpanas |
| 2025 | SIGMOD | ShapX Engine: A Demonstration of Shapley Value Approximations. | Suchit Gupte, John Paparrizos |
| 2024 | ICDE | An Interactive Dive into Time-Series Anomaly Detection. | Paul Boniol, John Paparrizos, Themis Palpanas |
| 2024 | ICDE | ADecimo: Model Selection for Time Series Anomaly Detection. | Paul Boniol, Emmanouil Sylligardos, John Paparrizos, Panos E. Trahanias, Themis Palpanas |
| 2024 | ICDE | Beyond the Dimensions: A Structured Evaluation of Multivariate Time Series Distance Measures. | Jens E. d'Hondt, Odysseas Papapetrou, John Paparrizos |
| 2024 | ICDE | AdaEdge: A Dynamic Compression Selection Framework for Resource Constrained Devices. | Chunwei Liu, John Paparrizos, Aaron J. Elmore |
| 2023 | EDBT | New Trends in Time Series Anomaly Detection. | Paul Boniol, John Paparrizos, Themis Palpanas |
| 2022 | ICDE | Fast Adaptive Similarity Search through Variance-Aware Quantization. | John Paparrizos, Ikraduya Edian, Chunwei Liu, Aaron J. Elmore, Michael J. Franklin |
| 2021 | CIDR | VergeDB: A Database for IoT Analytics on Edge Devices. | John Paparrizos, Chunwei Liu, Bruno Barbarioli, Johnny Hwang, Ikraduya Edian, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan |
| 2021 | SIGMOD | Good to the Last Bit: Data-Driven Encoding with CodecDB. | Hao Jiang, Chunwei Liu, John Paparrizos, Andrew A. Chien, Jihong Ma, Aaron J. Elmore |
| 2020 | SIGMOD | Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures. | John Paparrizos, Chunwei Liu, Aaron J. Elmore, Michael J. Franklin |
| 2019 | ICML | Band-limited Training and Inference for Convolutional Neural Networks. | Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin |
| 2016 | KDD | Detecting Devastating Diseases in Search Logs. | John Paparrizos, Ryen W. White, Eric Horvitz |
| 2015 | SIGMOD | k-Shape: Efficient and Accurate Clustering of Time Series. | John Paparrizos, Luis Gravano |