| Smoke: Fine-grained lineage at interactive speed F Psallidas, E Wu arXiv preprint arXiv:1801.07237, 2018 | 92 | 2018 |
| Extending relational query processing with ML inference K Karanasos, M Interlandi, D Xin, F Psallidas, R Sen, K Park, I Popivanov, ... arXiv preprint arXiv:1911.00231, 2019 | 80 | 2019 |
| S4: Top-k spreadsheet-style search for query discovery F Psallidas, B Ding, K Chakrabarti, S Chaudhuri Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 77 | 2015 |
| Vamsa: Automated provenance tracking in data science scripts MH Namaki, A Floratou, F Psallidas, S Krishnan, A Agrawal, Y Wu, Y Zhu, ... Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 69* | 2020 |
| Data science through the looking glass: Analysis of millions of github notebooks and ml. net pipelines F Psallidas, Y Zhu, B Karlas, J Henkel, M Interlandi, S Krishnan, B Kroth, ... ACM SIGMOD Record 51 (2), 30-37, 2022 | 63 | 2022 |
| Combining Design and Performance in a Data Visualization Management System. E Wu, F Psallidas, Z Miao, H Zhang, L Rettig, Y Wu, T Sellam CIDR, 2017 | 41 | 2017 |
| Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML A Agrawal, R Chatterjee, C Curino, A Floratou, N Gowdal, M Interlandi, ... arXiv preprint arXiv:1909.00084, 2019 | 38 | 2019 |
| Effective Event Identification in Social Media. F Psallidas, H Becker, M Naaman, L Gravano IEEE Data Eng. Bull. 36 (3), 42-50, 2013 | 35 | 2013 |
| Provenance for interactive visualizations F Psallidas, E Wu Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 1-8, 2018 | 20 | 2018 |
| Soc Web: Efficient Monitoring of Social Network Activities F Psallidas, A Ntoulas, A Delis International Conference on Web Information Systems Engineering, 118-136, 2013 | 17 | 2013 |
| Schema matching using pre-trained language models Y Zhang, A Floratou, J Cahoon, S Krishnan, AC Müller, D Banda, ... 2023 IEEE 39th International Conference on Data Engineering (ICDE), 1558-1571, 2023 | 15 | 2023 |
| Demonstration of smoke: A deep breath of data-intensive lineage applications F Psallidas, E Wu Proceedings of the 2018 International Conference on Management of Data, 1781 …, 2018 | 8 | 2018 |
| Nl2sql is a solved problem... not! A Floratou, F Psallidas, F Zhao, S Deep, G Hagleither, W Tan, J Cahoon, ... CIDR, 2024 | 5 | 2024 |
| OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance from Database Logs [Technical Report] F Psallidas, A Agrawal, C Sugunan, K Ibrahim, K Karanasos, ... arXiv preprint arXiv:2210.14047, 2022 | 3 | 2022 |
| SEIZE: Runtime Inspection for Parallel Dataflow Systems Y Li, M Interlandi, F Psallidas, W Wang, C Zaniolo IEEE Transactions on Parallel and Distributed Systems 32 (4), 842-854, 2020 | 2 | 2020 |
| Optimizing Data Pipelines for Machine Learning in Feature Stores R Liu, K Park, F Psallidas, X Zhu, J Mo, R Sen, M Interlandi, K Karanasos, ... Proceedings of the VLDB Endowment 16 (13), 4230-4239, 2023 | 1 | 2023 |
| SEIZE User Desired Moments: Runtime Inspection for Parallel Dataflow Systems Y Li, M Interlandi, F Psallidas, W Wang, C Zaniolo 2020 IEEE 40th International Conference on Distributed Computing Systems …, 2020 | 1 | 2020 |
| Rapidash: Efficient Detection of Constraint Violations Z Liu, S Deep, A Fariha, F Psallidas, A Tiwari, A Floratou Proceedings of the VLDB Endowment 17 (8), 2009-2021, 2024 | | 2024 |
| Linguistic schema mapping via semi-supervised learning A Floratou, JY Cahoon, SV Krishnan, AC Mueller, DH Banda, F Psallidas, ... US Patent App. 17/827,688, 2023 | | 2023 |
| Rapidash: Efficient Constraint Discovery via Rapid Verification Z Liu, S Deep, A Fariha, F Psallidas, A Tiwari, A Floratou arXiv preprint arXiv:2309.12436, 2023 | | 2023 |
Eugene WuColumbia UniversityBestätigte E-Mail-Adresse bei cs.columbia.edu
