Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie Van Deursen (2024), Is your anomaly detector ready for change? adapting aiops solutions to the real world, In Proceedings - 2024 IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI, CAIN 2024 p.222-233, ACM.

Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie Van Deursen (2023), Maintaining and Monitoring AIOps Models Against Concept Drift, In Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023 p.98-99, IEEE.

Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, Arie Van Deursen (2023), Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques, In Proceedings - 2023 IEEE/ACM 7th International Workshop on Green And Sustainable Software, GREENS 2023 p.17-18, IEEE.

Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan Rellermeyer (2022), Are Concept Drift Detectors Reliable Alarming Systems?: A Comparative Study, Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan (Eds.), In Proceedings of the 2022 IEEE International Conference on Big Data (Big Data) p.3364-3373, IEEE.

Alexandru Uta, Bogdan Ghit, Ankur Dave, Jan Rellermeyer, Peter Boncz (2022), In-Memory Indexed Caching for Distributed Data Processing, L. O'Conner (Eds.), In Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS) p.104-114, IEEE.

Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Nitinder Mohan, Jan S. Rellermeyer, More Authors (2022), Roadmap for edge AI: A Dagstuhl Perspective, In Computer Communication Review Volume 52 (2023) p.28-33.

V.J. van Rijn, Jan S. Rellermeyer (2021), A Fresh Look at the Architecture and Performance of Contemporary Isolation Platforms, In Proceedings of the 22nd ACM/IFIP International Middleware Conference, ACM DL.

Hao Li, Zixuan Li, Kenli Li, Jan S. Rellermeyer, Lydia Chen, Keqin Li (2021), SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition, In IEEE Transactions on Parallel and Distributed Systems Volume 32 p.1828-1841.

Yuanhao Xie, Luís Cruz, Petra Heck, Jan S. Rellermeyer (2021), Systematic Mapping Study on the Machine Learning Lifecycle, L. O'Conner (Eds.), In Proceedings - 2021 IEEE/ACM 1st Workshop on AI Engineering - Software Engineering for AI, WAIN 2021 p.70-73, IEEE.

Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, Jan S. Rellermeyer (2020), A Survey on Distributed Machine Learning, In ACM Computing Surveys (CSUR).