Nous consignons ici les contributions académiques et scientifiques de notre équipe de partenaires et de leurs stagiaires financés par le projet FONCER.
Ce répertoire témoigne du large éventail de recherches interdisciplinaires soutenues par le programme et des avancées collaboratives réalisées dans le domaine des systèmes de données durables.
(Dernière mise à jour : 25 août 2025)
S. Fathollahzadeh, E. Mansour, and M. Boehm. CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines. Proceedings of the VLDB Endowment (PVLDB), vol. 18, no. 4, 2025.
A. Aly, E. Mansour, and A. Youssef. OCR-APT: Reconstructing APT Stories from Audit Logs using Subgraph Anomaly Detection and LLMs. Proceedings of the ACM Conference on Computer and Communications Security (CCS), 2025.
R. Omar, O. Mangukiya, and E. Mansour. Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs. Proceedings of the ACM on Management of Data (Proc. ACM Manag. Data), vol. 3, no. 1, 2025.
O. Balmau, M. Böhm, A. Klimovic, P. Pietzuch, and P. Tözün. Resource‑Efficient Machine Learning (Dagstuhl Seminar 24311). Dagstuhl Reports, vol. 14, no. 7, pp. 153–169, 2025.
M. Zhang, F. Eliassen, A. Taherkordi, H.A. Jacobsen, Y. Li, and Y. Zhang. Self-Determination Theory and Deep Reinforcement Learning for Personalized Energy Trading in Smart Grid. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 55(6), 4216-4229, 2025.
I. Uwizeyimana and N. Enright Jerger. Carbon-Aware Server Replacement. Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2025.
G. Sehgal and S. Salihoğlu. NaviX: A Native Vector Index Design for Graph DBMSs With Robust Predicate-Agnostic Search Performance. Proceedings of the VLDB Endowment, 2025.
A. Chakraborty and S. Salihoğlu. Robust Recursive Query Parallelism in Graph Database Management Systems [Experiment, Analysis & Benchmark]. Proceedings of the VLDB Endowment, 2025.
M. Bachras and H.A. Jacobsen. Beyond Performance: Measuring the Environmental Impact of Analytical Databases. arXiv preprint, arXiv:2504.18980, 2025.
F. Farhour, A. Abdellatif, E. Mansour, and E. Shihab. A Weak Supervision-Based Approach to Improve Chatbots for Code Repositories. Proceedings of the ACM on Software Engineering, vol. 1, pp. 2378–2401, 2024.
A. Aly, S. Iqbal, A. Youssef, and E. Mansour. MEGR-APT: A Memory-Efficient APT Hunting System Based on Attack Representation Learning. IEEE Transactions on Information Forensics and Security, vol. 19, pp. 5257–5271, 2024.
M. Helali, N. Monjazeb, S. Vashisth, P. Carrier, A. Helal, A. Cavalcante, K. Ammar, K. Hose, and E. Mansour. KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science. Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2024.
H. Abdallah, W. Afandi, P. Kalnis, and E. Mansour. Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling. Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2024.
H. Woisetschläger, A. Erben, S. Wang, R. Mayer, and H.A. Jacobsen. Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. Proceedings of the Workshop on Data Management for End-to-End Machine Learning (DEEM@SIGMOD), pp. 39–50, 2024.
D. Teguia, J. Chen, S. Bitchebe, O. Balmau, and A. Tchana. vPIM: Processing‑in‑Memory Virtualization. Proceedings of the 25th International Middleware Conference, pp. 417–430, 2024.
R. Nouaji, S. Bitchebe, and O. Balmau. SpeedyLoader: Efficient Pipelining of Data Preprocessing and Machine Learning Training. Proceedings of the 4th Workshop on EuroMLSys (EuroMLSys ’24), 2024.
H. Woisetschläger, A. Erben, R. Mayer, S. Wang, and H.A. Jacobsen. FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems. Proceedings of the ACM/IFIP Middleware Conference, pp. 88–102, 2024.
Y. Zheng, C. Sacré, M. Shahrad, O. Lipchitz, Y. Gu, B. Kemme. G-View: View Management for Graph Databases. Proceedings of the VLDB Endowment (PVLDB), vol. 18, no. 6, pp. 1730-1742, 2025.
A. Erben, R. Mayer, and H.A. Jacobsen. How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study. Proceedings of the VLDB Endowment (PVLDB), vol. 17, no. 6, pp. 1214–1226, 2024.
Y. Mao, G. Zhang, Z. Liu, P. Nasirifard, S. Tijanic, and H.A. Jacobsen. Making CRDTs Not So Eventual. Proceedings of the VLDB Endowment (PVLDB), vol. 18, no. 2, pp. 349–362, 2024.
A. Plotnik, K. Ganesan, N. Enright Jerger, and M.C. Jeffery. Intergenerational Embodied Carbon. Proceedings of the Hot Topics in Ethics, Systems, and AI (HotEthics), 2024.
B. Dabak, M. Glenn, J. Liu, A. Buck, S. Yang, R. Calderbank, N. Enright Jerger, et al. Low-Energy Line Codes for On-Chip Networks. arXiv preprint, arXiv:2405.14783, 2024.
A. Mhedhbi, A. Deshpande, and S. Salihoğlu. Modern Techniques for Querying Graph-Structured Databases. Foundations and Trends in Databases, vol. 14, no. 2, pp. 72–185, 2024.
A. Usta, C. Liu, and S. Salihoğlu. Analysis of Open Government Datasets from a Data Design and Integration Perspective. Proceedings of the 27th International Conference on Extending Database Technology (EDBT), pp. 345–358, 2024.
S. Sahu and S. Salihoğlu. Optimizing Differential Computation for Large-Scale Graph Processing. Proceedings of the 7th Joint Workshop on Graph Data Management Experiences and Systems (GRADES/NDA), Article No. 4:1–4:9, 2024.
R. Zhang, H. Woisetschläger, S. Wang, and H.A. Jacobsen. MESS+: Energy-Optimal Inferencing in Language Model Zoos with SLAs. arXiv preprint, arXiv:2411.00889, 2024.
