Dr. Sven Weinzierl
Forschungsgebiete
- Algorithmic Research (z. B. Interpretable Machine Learning Algorithms)
- Design Science Research (z. B. Trustworthy Artificial Intelligence Systems)
- Behavioral Research (z. B. User Interaction with Explainable and Interpretable Artificial Intelligence)
Lehre
- Seminar Digitale Dienstleistungssysteme an der WiSo
- Forschungsmethodisches Seminar
- Process Analytics (Vorlesung)
CV
Berufserfahrung
Seit 08/2018 | Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Wissenschaftlicher Mitarbeiter | Chair of Digital Industrial Service Systems |
09/2017 – 12/2017 | DATEV eG Werkstudent | Artificial Intelligence / Machine Learning |
05/2017 – 07/2017 | MHP Management- und IT-Beratung GmbH Werkstudent | Predictive Analytics |
03/2015 – 07/2015 | MHP Management- und IT-Beratung GmbH Prakitkant | Business Intelligence |
01/2014 – 10/2014 | DATEV eG Werkstudent | Software Engineering |
08/2011 – 12/2013 | Ribe Holding GmbH & Co. KG Werkstudent | Software Development in Systems Integration |
Ausbildung
08/2018 – 04/2022 | Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Doktorand | Information Systems |
04/2016 – 06/2018 | Otto-Friedrich-Universität Bamberg Master of Science | Information Systems |
10/2012 – 03/2016 | Hochschule Ansbach Bachelor of Arts | Information Systems |
09/2008 – 07/2011 | Ribe Holding GmbH & Co. KG IHK Professional Training | IT Merchant |
Publikationen
Beiträge
2024
- Weinzierl S., Zilker S., Dunzer S., Matzner M.:
Machine learning in business process management: A systematic literature review
In: Expert Systems With Applications 253 (2024), Art.Nr.: 124181
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2024.124181
BibTeX: Download - Zilker S., Weinzierl S., Kraus M., Zschech P., Matzner M.:
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
In: Health Care Management Science 27 (2024), S. 136-167
ISSN: 1386-9620
DOI: 10.1007/s10729-024-09673-8
URL: https://link.springer.com/article/10.1007/s10729-024-09673-8#article-info
BibTeX: Download
2023
- Kraus M., Tschernutter D., Weinzierl S., Zschech P.:
Interpretable generalized additive neural networks
In: European Journal of Operational Research (2023)
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2023.06.032
BibTeX: Download - Oberdorf F., Schaschek M., Weinzierl S., Stein N., Matzner M., Flath C.:
Predictive end-to-end enterprise process network monitoring
In: Business & Information Systems Engineering (2023)
ISSN: 1867-0202
DOI: 10.1007/s12599-022-00778-4
BibTeX: Download
2022
- Weinzierl S., Wolf V., Pauli T., Beverungen D., Matzner M.:
Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data
In: Journal of Business Analytics 5 (2022), S. 76-100
ISSN: 2573-234X
DOI: 10.1080/2573234X.2021.1978337
URL: https://www.tandfonline.com/doi/full/10.1080/2573234X.2021.1978337
BibTeX: Download
2021
- Stierle M., Weinzierl S., Harl M., Matzner M.:
A technique for determining relevance scores of process activities using graph-based neural networks
In: Decision Support Systems 144 (2021), Art.Nr.: 113511
ISSN: 0167-9236
DOI: 10.1016/j.dss.2021.113511
URL: http://www.sciencedirect.com/science/article/pii/S016792362100021X
BibTeX: Download
2020
- Brunk J., Stottmeister J., Weinzierl S., Matzner M., Becker J.:
Exploring the effect of context information on deep learning business process predictions
In: Journal of Decision Systems (2020), S. 1-16
ISSN: 1246-0125
DOI: 10.1080/12460125.2020.1790183
BibTeX: Download - Harl M., Weinzierl S., Stierle M., Matzner M.:
Explainable predictive business process monitoring using gated graph neural networks
In: Journal of Decision Systems (2020), S. 1-16
ISSN: 1246-0125
DOI: 10.1080/12460125.2020.1780780
BibTeX: Download
Konferenzen
2024
- Harl M., Zilker S., Weinzierl S.:
Towards automated business process redesign in runtime using generative machine learning
European Conference on Information Systems (Paphos, Cyprus)
In: Proceedings of the 32nd European Conference on Information Systems 2024
BibTeX: Download - Ließmann A., Wang W., Weinzierl S., Zilker S., Matzner M.:
Transfer learning for predictive process monitoring
European Conference on Information Systems (Paphos, Cyprus)
In: Proceedings of the 32nd European Conference on Information Systems 2024
BibTeX: Download - Ließmann A., Zilker S., Weinzierl S., Sukhareva M., Matzner M.:
Predicting customer satisfaction in service processes using multilingual large language models
Hawaii International Conference on System Sciences (Waikiki, Honolulu, Hawaii)
In: Proceedings of the 57th Hawaii International Conference on System Sciences 2024
BibTeX: Download - Weinzierl S., Zilker S., Brunk J., Revoredo K., Matzner M., Becker J.:
Context-aware explanations of accurate predictions in service processes
Hawaii International Conference on System Sciences (Waikiki, Honolulu, Hawaii)
In: Proceedings of the 57th Hawaii International Conference on System Sciences 2024
BibTeX: Download
2023
- Arnold S., Yesilbas D., Weinzierl S.:
Driving context into text-to-text privatization
Annual Meeting of the Association for Computational Linguistics (Toronto)
In: Association for Computational Linguistics (Hrsg.): Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing 2023
DOI: 10.18653/v1/2023.trustnlp-1.2
URL: https://aclanthology.org/2023.trustnlp-1.2
BibTeX: Download - Arnold S., Yesilbas D., Weinzierl S.:
Guiding text-to-text privatization by syntax
Annual Meeting of the Association for Computational Linguistics (Toronto)
In: Association for Computational Linguistics (Hrsg.): Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing 2023
DOI: 10.18653/v1/2023.trustnlp-1.14
URL: https://aclanthology.org/2023.trustnlp-1.14/
BibTeX: Download - Drodt C., Weinzierl S., Matzner M., Delfmann P.:
Predictive Recommining: Learning relations between event log characteristics and machine learning approaches for supporting predictive process monitoring
International Conference on Advanced Information Systems Engineering (Zaragoza, 12. Juni 2023 - 16. Juni 2023)
In: Proceedings of the 35th International Conference on Advanced Information Systems Engineering Forum 2023
DOI: 10.1007/978-3-031-34674-3_9
BibTeX: Download - Zilker S., Weinzierl S., Zschech P., Kraus M., Matzner M.:
Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction
European Conference on Information Systems (Kristiansand, 13. Juni 2023 - 16. Juni 2023)
In: Proceedings of the 31st European Conference on Information Systems 2023
BibTeX: Download
2022
- Cabrera Pérez L., Weinzierl S., Zilker S., Matzner M.:
Text-aware predictive process monitoring with contextualized word embeddings
International Conference on Business Process Management (Münster)
In: Proceedings of the BPM 2022 International Workshops 2022
DOI: 10.1007/978-3-031-25383-6_22
BibTeX: Download - Weinzierl S., Bartelheimer C., Zilker S., Beverungen D., Matzner M.:
A method for predicting workarounds in business processes
Pacific Asia Conference on Information Systems (Taipei-Sydney, 5. Juli 2022 - 9. Juli 2022)
In: Proceedings of the 25th Pacific Asia Conference on Information Systems 2022
BibTeX: Download - Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
European Conference on Information Systems (Timisoara, 5. Juli 2022 - 9. Juli 2022)
In: Proceedings of the 30th European Conference on Information Systems 2022
BibTeX: Download
2021
- Drodt C., Weinzierl S., Matzner M., Delfmann P.:
The recomminder: A decision support tool for predictive business process monitoring
International Conference on Business Process Management (Rom)
In: Proceedings of the BPM 2021 Demonstration & Resources Track, Best BPM Dissertation Award, and Doctoral Consortium 2021
BibTeX: Download - Stierle M., Brunk J., Weinzierl S., Zilker S., Matzner M., Becker J.:
Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques
European Conference on Information Systems (Marrakesch)
In: Proceedings of the 29th European Conference on Information Systems 2021
BibTeX: Download - Weinzierl S.:
Exploring gated graph sequence neural networks for predicting next process activities
International Conference on Business Process Management (Rom)
In: Proceedings of the BPM 2021 International Workshops. 2021
DOI: 10.1007/978-3-030-94343-1_3
BibTeX: Download - Weinzierl S., Dunzer S., Tenschert J., Zilker S., Matzner M.:
Predictive business process deviation monitoring
European Conference on Information Systems (Marrakesch)
In: Proceedings of the 29th European Conference on Information Systems 2021
BibTeX: Download
2020
- Marx E., Stierle M., Weinzierl S., Matzner M.:
Closing the gap between smart manufacturing applications and data management
International Conference on Wirtschaftsinformatik (WI) (Potsdam, 9. März 2020 - 11. März 2020)
In: Proceedings of the 15th International Conference on Wirtschaftsinformatik (WI) 2020
DOI: 10.30844/wi_2020_u1-marx
URL: https://library.gito.de/2021/07/wi2020-community-tracks-9/
BibTeX: Download - Nguyen A., Chatterjee S., Weinzierl S., Schwinn L., Matzner M., Eskofier B.:
Time matters: Time-aware LSTMs for predictive business process monitoring
International Conference on Process Mining (Padua, 4. Oktober 2020 - 9. Oktober 2020)
In: Proceedings of the ICPM 2020 International Workshops 2020
DOI: 10.1007/978-3-030-72693-5_9
BibTeX: Download - Weinzierl S., Dunzer S., Zilker S., Matzner M.:
Prescriptive business process monitoring for recommending next best actions
International Conference on Business Process Management (Sevilla, 13. September 2020 - 18. September 2020)
In: Proceedings of the 18th International Conference on Business Process Management Forum 2020
DOI: 10.1007/978-3-030-58638-6_12
URL: https://link.springer.com/content/pdf/10.1007/978-3-030-58638-6_12.pdf
BibTeX: Download - Weinzierl S., Stierle M., Zilker S., Matzner M.:
A next click recommender system for web-based service analytics with context-aware LSTMs
Hawaii International Conference on System Sciences (Grand Wailea, Maui, Hawaii, 7. Januar 2020 - 10. Januar 2020)
In: Proceedings of the 53rd Hawaii International Conference on System Sciences 2020
DOI: 10.24251/HICSS.2020.190
URL: http://hdl.handle.net/10125/63929
BibTeX: Download - Weinzierl S., Wolf V., Pauli T., Beverungen D., Matzner M.:
Detecting workarounds in business processes — A deep learning method for analyzing event logs
European Conference on Information Systems (Marrakesch, 15. Juni 2020 - 17. Juni 2020)
In: Proceedings of the 28th European Conference on Information Systems 2020
URL: https://www.researchgate.net/publication/341180737_DETECTING_WORKAROUNDS_IN_BUSINESS_PROCESSES_-_A_DEEP_LEARNING_METHOD_FOR_ANALYZING_EVENT_LOGS
BibTeX: Download - Weinzierl S., Zilker S., Brunk J., Revoredo K., Matzner M., Becker J.:
XNAP: Making LSTM-based next activity predictions explainable by using LRP
International Conference on Business Process Management (Sevilla, 13. September 2020 - 18. September 2020)
In: Proceedings of the BPM 2020 International Workshops. 2020
DOI: 10.1007/978-3-030-66498-5_10
BibTeX: Download - Weinzierl S., Zilker S., Stierle M., Park G., Matzner M.:
From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events
Internationale Tagung Wirtschaftsinformatik (Potsdam, 8. März 2020 - 11. März 2020)
In: Proceedings of the 15th International Conference on Wirtschaftsinformatik 2020
DOI: 10.30844/wi_2020_c12-weinzierl
URL: https://library.gito.de/open-access-pdf/C12_Prescriptive_process_monitoring_-_a_technique_for_determining_next_best_actions_resub.pdf
BibTeX: Download
2019
- Weinzierl S., Revoredo K., Matzner M.:
Predictive business process monitoring with context information from documents
European Conference on Information Systems (Stockholm, 8. Juni 2019 - 14. Juni 2019)
In: Proceedings of the 27th European Conference on Information Systems 2019
URL: https://www.researchgate.net/publication/333245929_PREDICTIVE_BUSINESS_PROCESS_MONITORING_WITH_CONTEXT_INFORMATION_FROM_DOCUMENTS
BibTeX: Download
Berichte
Es wurden leider keine Publikationen gefunden.