Christian Haertel
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
10
Venues
6
Active years
2023–2026
Best venue rank
C
Where they publish
Papers
10 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ANT | On the creation of value achieved by harnessing large language models. | Daniel Staegemann, Matthias Pohl, Christian Haertel, Klaus Turowski |
| 2026 | ICSoft | Formalizing Model Selection in LLMOps: A Systematic UML-Based Process Model. | Maria Chernigovskaya, Abdulrahman Nahhas, Christian Haertel, Christian Daase, Klaus Turowski |
| 2025 | DATA | Democratizing the Access to Geospatial Data: The Performance Bottleneck of Unified Data Interfaces. | Matthias Pohl, Arne Osterthun, Joshua Reibert, Dennis Gehrmann, Christian Haertel, Daniel Staegemann, Klaus Turowski |
| 2025 | DATA | A Review on the Use of Large Language Models in the Context of Open Government Data. | Daniel Staegemann, Christian Haertel, Matthias Pohl, Klaus Turowski |
| 2025 | EDOC | Integration of Data Science Projects in Enterprise Architecture Modeling. | Matthias Pohl, Christian Haertel, Daniel Staegemann, Klaus Turowski |
| 2025 | IC3K | Guiding Improvement in Data Science: An Analysis of Maturity Models. | Christian Haertel, Tom Engelmann, Abdulrahman Nahhas, Christian Daase, Klaus Turowski |
| 2025 | IC3K | Elevating Data Science Maturity: Toward a Process Model that Harnesses MLOps. | Christian Haertel, Daniel Staegemann, Matthias Pohl, Klaus Turowski |
| 2024 | ICSoft | A Literature Survey on Pitfalls of Open-Source Dependency Management in Enterprise. | Andrey Kharitonov, Amro Abdalla, Abdulrahman Nahhas, Daniel Gunnar Staegemann, Christian Haertel, Christian Daase, Klaus Turowski |
| 2023 | IC3K | Toward Standardization and Automation of Data Science Projects: MLOps and Cloud Computing as Facilitators. | Christian Haertel, Christian Daase, Daniel Staegemann, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski |
| 2023 | ICINCO | A Meta-Review on the Use of Artificial Intelligence in the Context of Electrical Power Grid Operators. | Daniel Staegemann, Christian Haertel, Christian Daase, Matthias Pohl, Klaus Turowski |