Dr. David Broneske did his Bachelor and Master in Computer Science at the Otto-von-Guericke University Magdeburg, where he received his Ph.D. in 2019 and afterward started his Habilitation. From 2019 to 2020, he was the substitutional head of the chair of Database and Informationssystems at Hochschule Anhalt in Köthen. Since March 2021, he is the acting head of Department 4 "Infrastructures and Methods" of the German Centre for Higher Education Research and Science Studies (DZHW).
Dr. David Broneske
Research Area Research Infrastructure and Methods
Acting Head of Department
- +49 511 450670-454
- +49 511 450670-960
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Academic research fields
Research Data Management for Learning Analytics Data, Main-Memory Database Systems on Modern Hardware, Interactive Data Exploration and Visualization, Artificial Intelligence for Data Cleaning and Analysis
Projects
List of projects
Publications
List of publications
A mediation strategy for communication between an internal chat system and an open source chat system.Obionwu, C. V., Kanagaraj, R. R., Kalu, K. O., Broneske, D., Buch, A., Knopke, C., & Saake, G. (2024).A mediation strategy for communication between an internal chat system and an open source chat system. In Jon-Chao, H. (Hrsg.), New Technology in Education and Training, Select Proceedings of the 5th International Conference on Advance in Education and Information Technology (AEIT 2024) (S. 73-86). Singapore: Springer. https://doi.org/10.1007/978-981-97-3883-0_7 |
Exploring the predictive factors of heart disease using rare association rule mining.Darrab, S., Broneske, D., & Saake, G. (2024).Exploring the predictive factors of heart disease using rare association rule mining. Scientific Reports, 14. https://doi.org/10.1038/s41598-024-69071-6 Abstract
Cardiovascular diseases continue to be the leading cause of mortality worldwide, claiming a significant number of lives each year. Despite the advancements in predictive models, including logistic regression, neural networks, and random forests, these techniques often lack transparency and interpretability, limiting their practical application in clinical settings. To address this challenge, this research introduces EPFHD-RARMING, an innovative approach designed to enhance the understanding and predictability of heart disease through the discovery of rare and meaningful patterns. EPFHD-RARMING utilizes rare association rule mining to [...] Full Abstract: https://www.nature.com/articles/s41598-024-69071-6#citeas |
Expert agent guided learning with transformers and knowledge graphs.Obionwu, C. V., Chovatta Valappil, B. B., Genty, M., Jomy, M., Padmanabhan, V., ... & Saake, G. (2024).Expert agent guided learning with transformers and knowledge graphs. In SciTePress Science and Technology Publications (Hrsg.), Proceedings of the 13th International Conference on Data Science, Technology and Applications (DATA 2024) (S. 180-189). Setúbal, Portugal: Science and Technology Publications. |
Sharing software-evolution datasets: Practices, challenges, and recommendations.Broneske, D., Kittan, S., & Krüger, J. (2024).Sharing software-evolution datasets: Practices, challenges, and recommendations. In Association for Computing Machinery (Hrsg.), Proceedings of the ACM on Software Engineering (S. 2051-2074). New York, NY, United States: ACM. https://doi.org/10.1007/s11616-024-00852-9 |
Exploiting shared sub-expression and materialized view reuse for multi-query optimization.Gurumurthy, B., Bidarkar, V. R., Broneske, D., Pionteck, T., & Saake, G. (2024).Exploiting shared sub-expression and materialized view reuse for multi-query optimization. Information Systems Frontiers, A Journal of Research and Innovation. https://doi.org/10.1007/s10796-024-10506-w |
A design proposal for a unified B-epsilon-tree: Embracing NVM in memory hierarchies.Karim, S., Wünsche, J., Broneske, D., Kuhn, M., & Saake, G. (2024).A design proposal for a unified B-epsilon-tree: Embracing NVM in memory hierarchies. In Störl, U. (Hrsg.), GvDB 2024, Grundlagen von Datenbanken 2024, Proceedings of the 35th GI-Workshop Grundlagen von Datenbanken (Herdecke, Germany, May 22-24, 2024) (S. 43-50). Hagen: Fernuniversität Hagen, Databases and Information Systems. |
A case study on the development of the German Corona-Warn-App.Fawaz Enaya, M., Klingbeil, T., Krüger, J., Broneske, D., Feinbube, F., & Saake, G. (2024).A case study on the development of the German Corona-Warn-App. Journal of Systems and Software. https://doi.org/10.1016/j.jss.2024.112020 |
A domain specific students' assistance system for the provision of instructional feedback.Obionwu, C. V., Tiwari, T., Chovatta Valappil, B. B., Raikar, N., Walia, D. S., ... & Saake, G. (2024).A domain specific students' assistance system for the provision of instructional feedback. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2023 International Conference on Machine Learning and Applications (ICMLA) (S. 2065-2070). Jacksonville, Florida, USA: IEEE. https://doi.org/10.1109/ICMLA58977.2023.00312 |
Knowledge distillation for quantized vehicle sensor data.Vox, C., Niemann, O., Broneske, D., Piewek, J., Sass, A. U., & Saake, G. (2024).Knowledge distillation for quantized vehicle sensor data. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2023 International Conference on Machine Learning and Applications (ICMLA) (S. 908-915). Jacksonville, Florida, USA: IEEE. https://doi.org/10.1109/ICMLA58977.2023.00134 |
Enforcing right to be forgotten in cloud-based data lakes.Bhardwaj, P., Darrab, S., Broneske, D., Klose, I., & Saake, G. (2024).Enforcing right to be forgotten in cloud-based data lakes. In Arai, K. (Hrsg.), Advances in Information and Communication (FICC 2024) (S. 220-234). Cham: Springer. https://doi.org/10.1007/978-3-031-53963-3_16 |
An evolutionary algorithm with heuristic operator for detecting protein complexes in protein interaction networks with negative controls.Abbas, M. N., Attea, B. A., Broneske, D., & Saake, G. (2024).An evolutionary algorithm with heuristic operator for detecting protein complexes in protein interaction networks with negative controls. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3367746 Abstract
Computational biology research faces a formidable challenge in the detection of complexes within protein-protein interaction (PPI) networks, critical for unraveling cellular processes, predicting functions of uncharacterized proteins, and diagnosing diseases. While evolutionary algorithms (EAs), particularly state-of-the-art methods, often partition PPI networks based on graph properties or biological semantics, their resilience to noisy or missing interactions remains an underexplored territory. In this paper, we propose a groundbreaking heuristic operator, termed "strong neighbor-node migration", specifically designed to elevate solution quality [...] Full Abstract: https://ieeexplore.ieee.org/document/10440281 |
Framing and BERTology: A data-centric approach to integration of linguistic features into transformer-based pre-trained language models.Avetisyan, H., Safikhani, P., & Broneske, D. (2024).Framing and BERTology: A data-centric approach to integration of linguistic features into transformer-based pre-trained language models. In Arai, K. (Hrsg.), Intelligent Systems and Applications (S. 81-90). Cham: Springer. https://doi.org/10.1007/978-3-031-47718-8 |
Clustering graph data: the roadmap to spectral techniques.Mondal, R., Ignatova, E., Walke, D., Broneske, D., Saake, G., & Heyer, R. (2024).Clustering graph data: the roadmap to spectral techniques. Discover Artificial Intelligence, 4(7), 1-22. https://doi.org/10.1007/s44163-024-00102-x Abstract
Graph data models enable efficient storage, visualization, and analysis of highly interlinked data, by providing the benefits of horizontal scalability and high query performance. Clustering techniques, such as K-means, hierarchical clustering, are highly beneficial tools in data mining and machine learning to find meaningful similarities and differences between data points. Recent developments in graph data models, as well as clustering algorithms for graph data, have shown promising results in image segmentation, gene data analysis, etc. This has been primarily achieved through research and development of algorithms in the field of spectral theory, [...] Full abstract: https://doi.org/10.1007/s44163-024-00102-x |
Anomaly detection algorithms: Comparative analysis and explainability perspectives.Darab, S., Allipilli, H., Ghani, S., Changaramkulath, H., Koneru, S., Broneske, D., & Saake, G. (2023).Anomaly detection algorithms: Comparative analysis and explainability perspectives. In D. Benavides-Prado et al. (Hrsg.), Data Science and Machine Learning, 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings (S. 90-104). Singapore: Springer Nature. |
Presentations
List of presentations & conferences
A common Storage engine for modern Memory and Storage Hierarchies (SMASH).Karim, S., Wünsche, J., Kuhn, M., Broneske, D., & Saake, G. (2024, September).A common Storage engine for modern Memory and Storage Hierarchies (SMASH). Vortrag im Rahmen des SPP 2377 Annual Meeting 2024, Universität Osnabrück. |
Expert agent guided learning with transformers and knowledge graphs.Obionwu, C. V., Chovatta Valappil, B. B., Genty, M., Jomy, M., Padmanabhan, V., ... & Saake, G. (2024, Juli).Expert agent guided learning with transformers and knowledge graphs. Vortrag auf der Konferenz 13th International Conference on Data Science, Technology and Applications (DATA 2024), Dijon, Frankreich. |
Mitigating the risk of bots in web surveys recruited via social media.Shahania, S., Claaßen, J., Höhne, J. K., & Broneske, D. (2024, März).Mitigating the risk of bots in web surveys recruited via social media. Vortrag im Department of Methodology and Statistics, Utrecht University (The Netherlands), Utrecht. |
How to incorporate AI interviewers in contemporary web surveys?Höhne, J. K., Broneske, D., Neuert, C., & Claaßen, J. (2024, Januar).How to incorporate AI interviewers in contemporary web surveys? Vortrag im Rahmen des Events 'Going online: using video interviewing in survey research', The Royal Statistical Society, London, UK. |
A mediation strategy for communication between an internal chat system and an open source chat system.Obionwu, C. V., Kanagaraj, R. R., Oji Kalu, K., Broneske, D., Buch, A., Knopke, C., & Saake, G. (2024, Januar).A mediation strategy for communication between an internal chat system and an open source chat system. Vortrag auf der Konferenz 5th International Conference on Advances in Education and Information Technology (AEIT 2024), Nagoya, Japan. |
Laughing out loud – Exploring AI-generated and human-generated humor.Avetisyan, H., Safikhani, P., & Broneske, D. (2023, Dezember).Laughing out loud – Exploring AI-generated and human-generated humor. Vortrag auf der Konferenz International Conference on NLP & Artificial Intelligence Techniques (NLAI 2023), Computer Science & Information Technology (CS & IT), Sydney, Australia. |
Anomaly detection algorithms: Comparative analysis and explainability perspectives.Darab, S., Allipilli, H., Ghani, S., Changaramkulath, H., Koneru, S., Broneske, D., & Saake, G. (2023, Dezember).Anomaly detection algorithms: Comparative analysis and explainability perspectives. Vortrag auf der Konferenz The 21st Australasian Data Science and Machine Learning Conference (AUSDM23), Auckland, New Zealand. |
WISHFUL - Website Extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage.Shahania, S., Spiliopoulou, M., & Broneske, D. (2023, Dezember).WISHFUL - Website Extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage. Vortrag auf der Konferenz The 25th International Conference on Information Integration and Web Intelligence (iiWAS 2023) and The 21st International Conference on Advances in Mobile Computing & Multimedia Intelligence (MoMM2023), Denpasar, Bali, Indonesien. |
FPGA-integrated bag of little bootstraps accelerator for approximate database query processing.Burtsev, V., Wilhelm, M., Drewes, A., Gurumurthy, B., Broneske, D., Pionteck, T., & Saake, G. (2023, September).FPGA-integrated bag of little bootstraps accelerator for approximate database query processing. Vortrag im Rahmen des 19th International Symposium on Applied Reconfigurable Computing (ARC 2023), Cottbus. |
Framing and BERTology: A data-centric approach to integration of linguistic features into transformer-based pre-trained language models.Avetisyan, H., Safikhani, P., & Broneske, D. (2023, September).Framing and BERTology: A data-centric approach to integration of linguistic features into transformer-based pre-trained language models. Vortrag auf der Konferenz Intelligent Systems Conference (IntelliSys 2023), Amsterdam, The Netherlands. |
Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system.Obionwu, C. V., Abbas, S. M. L., Padmanabhan, V., Tiwari, T., Broneske, D., & Saake, G. (2023, Juli).Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system. Vortrag auf der Konferenz 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023), Teneriffa, Spanien. |
A strategy for retrospective evaluation of students SQL learning engagements.Obionwu, C. V., Kalu, K. O., Blockhaus, P., Broneske, D., & Saake, G. (2023, Juli).A strategy for retrospective evaluation of students SQL learning engagements. Vortrag auf der Konferenz 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023), Teneriffa, Spanien. https://doi.org/10.1109/ICECCME57830.2023.10252347 |
A strategy for structuring teams collaboration in university course projects.Obionwu, C. V., Karl, M., Broneske, D., Hawlitschek, A., Blockhaus, P., & Saake, G. (2023, Juli).A strategy for structuring teams collaboration in university course projects. Vortrag auf der Konferenz 20th International Conference on Smart Business Technologies (ICSBT 2023), Rom, Italien. |
Curriculum Vitae
Since 03/2021
Acting Head of Department 4 "Infrastructures and Methods" of the German Centre for Higher Education Research and Science Studies (DZHW)
04/2020 - 02/2021
Post-Doc at Otto-von-Guericke University Magdeburg
10/2019 - 03/2020
Substitutional Professor at Hochschule Anhalt - Chair of Database and Information Systems
06/2019 - 09/2019
Post-Doc at Otto-von-Guericke University Magdeburg
08/2013 - 05/2019
PhD Student at Otto-von-Guericke University Magdeburg
2008 - 2013
Bachelor and Master Studies in "Computer Science", Otto-von-Guericke University Magdeburg
