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 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. |
WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage.Shahania, S., Spiliopoulou, M., & Broneske, D. (2023).WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage. In Delir Haghighi, P. et al. (Hrsg.), Information Integration and Web Intelligence (iiWAS 2023) (S. 20-26). Cham: Springer. https://doi.org/10.1007/978-3-031-48316-5_3 Abstract
Extracting information from diverse websites is increasingly important, especially for analyzing vast data sets to detect trends, gain insights. By studying job ads, researchers can monitor employer demand shifts, assisting policymakers in aiding affected workers and industries. However, extraction faces challenges like varied website formats, dynamic content, and duplicate data. This study introduces a method for extracting data from diverse private university websites involving keyword identification, website categorization, and extraction pipelines. |
Large language models and low-resource languages: An examination of Armenian NLP.Avetisyan, H., & Broneske, D. (2023).Large language models and low-resource languages: An examination of Armenian NLP. Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings), 2023, 199-210. |
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).Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (S. 1-6). Tenerife, Spain: IEEE. https://doi.org/10.1109/ICECCME57830.2023.10252423 |
A strategy for retrospective evaluation of students SQL learning engagements.Obionwu, C. V., Kalu, K. O., Blockhaus, P., Broneske, D., & Saake, G. (2023).A strategy for retrospective evaluation of students SQL learning engagements. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023) (S. 1-7). Tenerife, Spain: IEEE. https://doi.org/10.1109/ICECCME57830.2023.10252347 |
Decoding the encoded - Linguistic secrets of language models: A systematic literature review.Avetisyan, H., & Broneske, D. (2023).Decoding the encoded - Linguistic secrets of language models: A systematic literature review. In D. C. Wyld & D. Nagamalai (Hrsg.), Computer Science & Information Technology (CS & IT) (S. 67-88). Chennai, Tamil Nadu, India: AIRCC Publishing Corporation. |
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).FPGA-integrated bag of little bootstraps accelerator for approximate database query processing. In F. Palumbo, G. Keramidas, N. Voros, & P. C. Diniz (Hrsg.), Applied Reconfigurable Computing. Architectures, Tools, and Applications (ARC 2023). Lecture Notes in Computer Science (S. 115-130). Cham: Springer. |
Presentations
List of presentations & conferences
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. |
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. |
What happens when two multi-query optimization paradigms combine?Gurumurthy, B., Bidarkar, V. R., Broneske, D., Pionteck, T., & Saake, G. (2023, Juli).What happens when two multi-query optimization paradigms combine? Vortrag auf der Konferenz European Conference on Advances in Databases and Information Systems (ADBIS 2023), Barcelona, Spanien. |
Towards a future of fully self-optimizing query engines.Blockhaus, P., Campero Durand, G., Broneske, D., & Saake, G. (2023, Juni).Towards a future of fully self-optimizing query engines. Vortrag im Rahmen des 34th Workshop on Foundations of Database Systems (Grundlagen von Datenbanken GVDB23), Calw. |
Vertical vectorized hashing for faster group-by aggregation.Nijalingappa, S., Gurumurthy, B., Broneske, D., & Saake, G. (2023, April).Vertical vectorized hashing for faster group-by aggregation. Vortrag auf dem Workshop Joint International Workshop on Big Data Management on Emerging Hardware and Data Management on Virtualized Active Systems (HardBD & Active'23), Anaheim, California, USA. |
Klausurtagung des DZHW-Forschungsclusters " Open Science " .
Workshop Klausurtagung des DZHW-Forschungsclusters "Open Science", DZHW, Berlin. |
Second Workshop on Novel Data Management Ideas on Heterogeneous (Co-)Processors (NoDMC).Broneske, D., & Habich, D. (2023, März).Workshop Second Workshop on Novel Data Management Ideas on Heterogeneous (Co-)Processors (NoDMC) im Rahmen der 20th Conference on Database Systems for Business, Technology and Web (BTW 2023), TU Dresden, Dresden. |
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
