| 2025 | IPCCC | Adaptive LLM Routing for Scientific Workflows: Predicting Query Complexity to Optimize Cost. | Jonas Thierfeldt, Dominik Scheinert, Thorsten Wittkopp, Odej Kao |
| 2024 | CLUSTER | Sizey: Memory-Efficient Execution of Scientific Workflow Tasks. | Jonathan Bader, Fabian Skalski, Fabian Lehmann, Dominik Scheinert, Jonathan Will, Lauritz Thamsen, Odej Kao |
| 2023 | IC2E | Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems. | Dominik Scheinert, Fabian Casares, Morgan K. Geldenhuys, Kevin Styp-Rekowski, Odej Kao |
| 2023 | IPCCC | Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics. | Dominik Scheinert, Philipp Wiesner, Thorsten Wittkopp, Lauritz Thamsen, Jonathan Will, Odej Kao |
| 2023 | SSDBM | Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing? | Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Odej Kao |
| 2022 | EuroPar | Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads. | Philipp Wiesner, Dominik Scheinert, Thorsten Wittkopp, Lauritz Thamsen, Odej Kao |
| 2022 | FedCSIS | Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing. | Morgan Geldenhuys, Benjamin J. J. Pfister, Dominik Scheinert, Lauritz Thamsen, Odej Kao |
| 2022 | IC2E | Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing. | Jonathan Will, Lauritz Thamsen, Jonathan Bader, Dominik Scheinert, Odej Kao |
| 2022 | IC2E | Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning. | Houkun Zhu, Dominik Scheinert, Lauritz Thamsen, Kain Kordian Gontarska, Odej Kao |
| 2022 | ICFEC | Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams. | Soeren Becker, Dominik Scheinert, Florian Schmidt, Odej Kao |
| 2022 | IPCCC | Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures. | Jonathan Bader, Fabian Lehmann, Alexander Groth, Lauritz Thamsen, Dominik Scheinert, Jonathan Will, Ulf Leser, Odej Kao |
| 2022 | ICWS | Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads. | Morgan K. Geldenhuys, Dominik Scheinert, Odej Kao, Lauritz Thamsen |
| 2021 | CLUSTER | Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. | Dominik Scheinert, Lauritz Thamsen, Houkun Zhu, Jonathan Will, Alexander Acker, Thorsten Wittkopp, Odej Kao |
| 2021 | EuroPar | Rafiki: Task-Level Capacity Planning in Distributed Stream Processing Systems. | Benjamin J. J. Pfister, Wolf S. Lickefett, Jan Nitschke, Sumit Paul, Morgan K. Geldenhuys, Dominik Scheinert, Kain Kordian Gontarska, Lauritz Thamsen |
| 2021 | IC2E | Evaluation of Load Prediction Techniques for Distributed Stream Processing. | Kain Kordian Gontarska, Morgan Geldenhuys, Dominik Scheinert, Philipp Wiesner, Andreas Polze, Lauritz Thamsen |
| 2021 | IC2E | C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. | Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Jonathan Bader, Odej Kao |
| 2021 | IPCCC | Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation. | Dominik Scheinert, Houkun Zhu, Lauritz Thamsen, Morgan K. Geldenhuys, Jonathan Will, Alexander Acker, Odej Kao |
| 2021 | ICSOC | LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision. | Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Alexander Acker |
| 2021 | ICSOC | A Taxonomy of Anomalies in Log Data. | Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Odej Kao |
| 2021 | Middleware | Let's wait awhile: how temporal workload shifting can reduce carbon emissions in the cloud. | Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kain Kordian Gontarska, Lauritz Thamsen |
| 2020 | ICSOC | TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services. | Dominik Scheinert, Alexander Acker |