Sandra Zilker

2010 - 2014 Bachelorstudium: Bachelor of Science Wirtschaftswissenschaften (Julius-Maximilians-Universität Würzburg)

2014 - 2016 Masterstudium: Master of Science Wirtschaftsinformatik (Julius-Maximilians-Universität Würzburg)

2016 - 2018 Merchandise Planner & Allocator (comma, GmbH, s.Oliver Group)

2018 - 2023 Wissenschaftliche Mitarbeiterin und Promotion (Friedrich-Alexander-Universität Erlangen-Nürnberg)

2023 - 2024 Akademische Rätin auf Zeit (Friedrich-Alexander-Universität Erlangen-Nürnberg)

Geschäftsprozessmanagemet, Business Analytics und deren Schnittstelle

• Predictive und Prescriptive Business Process Monitoring
• Explainable und Interpretable AI

Module im SS24:

• Grundlagen der Wirtschaftsinformatik
• Geschäftsprozessmanagement
• Angewandte Prozessanalyse

Kontaktieren Sie mich gerne, wenn Sie Interesse an einer Abschlussarbeit in den Bereichen "Geschäftsprozessmanagement", "Business Analytics" oder an deren Schnittstelle haben.

• Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., and Becker J. (2024). “Context-aware explanations of accurate predictions in service processes”, In: Proceedings of the 57th Hawaii International Conference on System Sciences, Honolulu, HI, USA: University of Hawaiʻi at Mānoa Library, pp. 1498–1507.
• Liessmann, A., Zilker, S., Weinzierl, S., Sukhareva, M., and Matzner, M. (2024). “Predicting Customer Satisfaction in Service Processes using Multilingual Large Language Models”. In: Proceedings of the 57th Hawaii International Conference on System Sciences, Honolulu, HI, USA: University of Hawaiʻi at Mānoa Library, pp. 1488–1497.
• Dunzer, S., Tang, W., Höchstädter, N., Zilker, S., and Matzner, M. (2023). “Design Principles for Using Business Process Management Systems”. In: Proceedings of the 16th Workshop on Business Process Management and Social Software, International Conference on Business Process Management, Utrecht, The Netherlands, pp. 217–228.
• Zilker, S., Weinzierl, S., Zschech, P., Kraus, M., and Matzner, M. (2023). “Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction”. In: Proceedings of the 31st European Conference on Information Systems. Kirstiansand, Norway: Association for Information Systems, pp. 1–16.
• Cabrera, L., Weinzierl, S., Zilker, S., and Matzner, M. (2022). “Text-aware Predictive Process Monitoring with Contextualized Word Embeddings”. In: Proceedings of 20th International Conference on Business Process Management (Workshops). Münster, Germany: Springer, pp. 303–314.
• Weinzierl, S., Bartelheimer, C., Zilker, S., Beverungen, D., and Matzner, M. (2022). “A Method for Predicting Workarounds in Business Processes”. In: Proceedings of the 25th Pacific Asia Conference on Information Systems. Taipei, China/ Sydney, Australia/ Virtual: Association for Information Systems, pp. 1–9.
• Zilker, S. (2022). “Designing a Method for Resource-specific Next Activity Prediction in Business Processes”. In: Proceedings of the 25th Pacific Asia Conference on Information Systems. Taipei, China/ Sydney, Australia/ Virtual: Association for Information Systems, pp. 1–9.
• Zilker, S., Marx, E., Stierle, M., and Matzner, M. (2022). “Process Mining for Advanced Service Analytics — From Process Efficiency to Customer Encounter and Experience”. In: Proceedings of the 55th Hawaii International Conference on System Sciences. Virtual: University of Hawaiʻi at Mānoa Library, pp. 1903–1912.
• Zschech, P., Weinzierl, S., Hambauer, N., Zilker, S., and Kraus, M. (2022). “GAM(e) Changer or Not? An Evaluation of Interpretable Machine Learning Models Based on Additive Model Constraints”. In: Proceedings of the 30th European Conference on Information Systems. Timisoara, Romania: Association for Information Systems, pp. 1–18.
• Dunzer, S., Zilker, S., Marx, E., Grundler, V., and Matzner, M. (2021). “The Status Quo of Process Mining in the Industrial Sector”. In: Proceedings of the 16th International Conference on Wirtschaftsinformatik. Essen, Germany: Association for Information Systems, pp. 1–17.
• Ochmann, J., Zilker, S., and Laumer, S. (2021). “The Evaluation of the Black Box Problem for AI-based Recommendations: An Interview-based Study”. In: Proceedings of the 16th International Conference on Wirtschaftsinformatik. Essen, Germany: Association for Information Systems, pp. 1–16.
• Stierle, M., Brunk, J., Weinzierl, S., Zilker, S., Matzner, M., and Becker, J. (2021). “Bringing Light into the Darkness – A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques”. In: Proceedings of the 29th European Conference on Information Systems. Marrakech, Morocco: Association for Information Systems, pp. 1–12.
• Weinzierl, S., Dunzer, S., Tenschert, J., Zilker, S., and Matzner, M. (2021). “Predictive Business Process Deviation Monitoring”. In: Proceedings of the 29th European Conference on Information Systems. Marrakech, Morocco: Association for Information Systems, pp. 1–16.
• Ochmann, J., Michels, L., Zilker, S., Tiefenbeck, V., and Laumer, S. (2020a). “The Influence of Algorithm Aversion and Anthropomorphic Agent Design on the Acceptance of AI-based Job Recommendations”. In: Proceedings of the 41st International Conference on Information Systems. Hyderabad, India: Association for Information Systems, pp. 1–17.
• Ochmann, J., Zilker, S., and Laumer, S. (2020b). “Job Seekers’ Artificial Intelligence-related Black Box Concerns”. In: Proceedings of the 2020 International Conference on Computers and People Research. Nuremberg, Germany: Association for Computing Machinery, pp. 101–102.
• Stierle, M., Zilker, S., Dunzer, S., Tenschert, J., and Karagegova, G. (2020). “Design Principles for Comprehensible Process Discovery in Process Mining”. In: Proceedings of the 28th European Conference on Information Systems. Marrakech, Morocco: Association for Information Systems, pp. 1–16.
• Weinzierl, S., Dunzer, S., Zilker, S., and Matzner, M. (2020). “Prescriptive Business Process Monitoring for Recommending Next Best Actions”. In: Proceedings of the 18th International Conference on Business Process Management (Forum). Seville, Spain: Springer, pp. 193–209.
• Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., and Becker, J. (2020c). “XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP”. In: Proceedings of the 18th International Conference on Business Process Management (Workshops). Seville, Spain: Springer, pp. 129–141.
• Weinzierl, S., Zilker, S., Stierle, M., Matzner, M., and Park, G. (2020). “From Predictive to Prescriptive Process Monitoring: Recommending the Next Best Actions Instead of Calculating the Next Most Likely Events”. In: Proceedings of the 15th International Conference on Wirtschaftsinformatik. Potsdam, Germany: Association for Information Systems, pp. 364–368.
• Weinzierl, S., Stierle, M., Zilker, S., and Matzner, M. (2020b). “A Next Click Recommender System for Web-based Service Analytics with Context-aware LSTMs”. In: Proceedings of the 53rd Hawaii International Conference on System Sciences. Maui, HI, USA: University of Hawaiʻi at Mānoa Library, pp. 1542–1551.