Sven Weinzierl
Forschungsschwerpunkte
- Predictive Process Analytics with Deep Learning
- Prescriptive Process Analytics with Deep Learning
Lehre
- Forschungsmethodisches Seminar (Bachelor)
- Seminar Wirtschaftsinformatik (Bachelor)
- TS410 – Integrated Business Processes in SAP S/4HANA (Training)
CV
Arbeitserfahrung
Seit 08/2018 | Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Wissenschaftlicher Mitarbeiter | Lehrstuhl für 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
Praktikant | Business Intelligence |
01/2014 – 10/2014 | DATEV eG
Werkstudent | Software Engineering |
08/2011 – 12/2013 | Ribe Holding GmbH & Co. KG
Werkstudent | Software Development in Systemintegration |
Ausbildung
Seit 08/2018 | Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Doktorand | Wirtschaftsinformatik |
04/2016 – 06/2018 | Otto-Friedrich-Universität Bamberg
Master of Science | Wirtschaftsinformatik |
10/2012 – 03/2016 | Hochschule Ansbach
Bachelor of Arts | Wirtschaftsinformatik |
09/2008 – 07/2011 | Ribe Holding GmbH & Co. KG
IHK Berufsausbildung | Informatikkaufmann |
Forschungsbeiträge
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 (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 - Marx E., Stierle M., Weinzierl S., Matzner M.:
Closing the Gap between Smart Manufacturing Applications and Data Management
15th International Conference on Wirtschaftsinformatik (Potsdam)
DOI: 10.30844/wi_2020_u1-marx
URL: https://library.gito.de/open-access-pdf/U1_Marx-Closing_the_Gap_between_Smart_Manufacturing_Applications_and_Data_Management-525_c.pdf
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 1st International Workshop on Leveraging Machine Learning in Process Mining 2020
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 4th International Workshop on Artificial Intelligence for Business Process Management 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 Businss 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
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Institut für Wirtschaftsinformatik
Fachbereich Wirtschafts- und Sozialwissenschaften
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