Publications

Ethan Seow, Yan Tong, Eli Baum, Sam Buxbaum, Muhammad Faisal, John Liagouris, Vasiliki Kalavri, and Mayank Varia. QueryShield: Cryptographically Secure Analytics in the Cloud. In the 2024 International Conference on Management of Data (SIGMOD/PODS ’24). [pdf] [code]
Yuhang Song, Po Hao Chen, Yuchen Lu, Naima Abrar and Vasiliki Kalavri. In situ neighborhood sampling for large-scale GNN training. Best Short Paper Award. In Proceedings of the 20th International Workshop on Data Management on New Hardware (DaMoN ’24). [pdf] [code]
Sonia Horchidan, Po Hao Chen, Emmanouil Kritharakis, Paris Carbone and Vasiliki Kalavri. Crayfish: Navigating the Labyrinth of Machine Learning Inference in Stream Processing Systems. In the 27th International Conference on Extending Database Technology (EDBT’24). [pdf] [code]

Marios Fragkoulis, Paris Carbone, Vasiliki Kalavri, and Asterios Katsifodimos. A Survey on the Evolution of Stream Processing Systems. In the VLDB Journal. [pdf] [cite]
Muhammad Faisal, Jerry Zhang, John Liagouris, Vasiliki Kalavri, and Mayank Varia. TVA: A multi-party computation system for secure and expressive time series analytics. In 32nd USENIX Security Symposium (Security’23). [pdf] [technical report] [code]
John Liagouris, Vasiliki Kalavri, Muhammad Faisal and Vayank Varia. Secrecy: Secure collaborative analytics in untrusted clouds. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI’23). [pdf] [code]

Michał Zwolak, Zainab Abbas, Sonia Horchidan, Paris Carbone and Vasiliki Kalavri. GCNSplit: Bounding the State of Streaming Graph Partitioning. In Proceedings of the International Workshop on Exploiting Artificial Intelligence Techniques for Data Management 2022 (aiDM’22, co-located with SIGMOD’22). [pdf]
Sonia Horchidan, Emmanouil Kritharakis, Vasiliki Kalavri, Paris Carbone. Evaluating Model Serving Strategies over Streaming Data. Best Paper Award. In Proceedings of the International Workshop on Data Management for End-to-End Machine Learning 2022 (DEEM’22, co-located with SIGMOD’22). [pdf]
Yuanli Wang, Baiqing, Lyu and Vasiliki Kalavri. The Non-Expert Tax: Quantifying the cost of auto-scaling in Cloud-based data stream analytics. In Proceedings of the International Workshop on Big Data in Emergent Distributed Environments 2022 (BiDEDE’22, co-located with SIGMOD’22). [pdf] [cite]
Esmail Asyabi, Yuanli Wang, John Liagouris, Vasiliki Kalavri, and Azer Bestavros. 2022. A new benchmark harness for systematic and robust evaluation of streaming state stores. In Proceedings of the Seventeenth European Conference on Computer Systems (EuroSys ’22). [pdf]
Massimo Perini, Giorgia Ramponi, Paris Carbone and Vasiliki Kalavri. Learning on Streaming Graphs with Experience Replay. In Proceedings of the 37th Annual ACM Symposium on Applied Computing. [preprint pdf].

M. Besta, M. Fischer, V. Kalavri, M. Kapralov and T. Hoefler. Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems. In IEEE Transactions on Parallel and Distributed Systems, doi: 10.1109/TPDS.2021.3131677. [pdf]
Raza Ali, Matta Ibrahim, Akhtar Nabeel, Kalavri Vasiliki, Isahagian Vatche. SoK: Function-as-a-Service: From An Application Developer’s Perspective. In Journal of Systems Research (JSys). September 2021. [pdf]
Liagouris, J., Kalavri, V., Faisal, M. and Varia, M., 2021. Secrecy: Secure collaborative analytics on secret-shared data. arXiv preprint arXiv:2102.01048. [pdf]
Sakr S, Bonifati A, Voigt H, Iosup A et al. The Future is Big Graphs! A Community View on Graph Processing Systems. In Communications of the ACM, 2021 [pdf]

Fragkoulis, M., Carbone, P., Kalavri, V. and Katsifodimos, A., 2020. A Survey on the Evolution of Stream Processing Systems. arXiv preprint arXiv:2008.00842. [pdf]
Kalavri, V. and Liagouris, J., 2020. In support of workload-aware streaming state management. Outstanding New Research Direction Award. In 12th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 20). [pdf]
Carbone, P., Fragkoulis, M., Kalavri, V. and Katsifodimos, A., 2020, June. Beyond analytics: The evolution of stream processing systems. In Proceedings of the 2020 ACM SIGMOD international conference on Management of data (pp. 2651-2658). [pdf]
Besta, M., Fischer, M., Kalavri, V., Kapralov, M. and Hoefler, T., 2020. Practice of streaming and dynamic graphs: Concepts, models, systems, and parallelism. Computing Research Repository (CoRR). [pdf]