Myriam Schaschek
Sprechstunde: nach Vereinbarung
Forschungsinteressen:
- Data-driven Decision Support in Organizations
- Data and Process Analytics
- Artificial Intelligence for Process Analytics
- Generative Artificial Intelligence - Use, Trust and Impact
- Hyperautomation
Forschungsprojekte:
- Plattform für das integrierte Management von Kollaborationen in Wertschöpfungsnetzwerken - PIMKoWe
- Prediction of Industrial Processes through Explainable Artificial Intelligence - pipeAI
Publikationen:
- Schaschek, M., Gwinner, F., Hein, B. & Winkelmann, A. (2023). From Black Box to Glass Box: Evaluating the Faithfulness of Process Predictions with GCNNs. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Workshop and Tutorial Track, forthcoming.
- Tomitza, C., Schaschek, M., Straub, L. & Winkelmann, A. (2023). What is the Minimum to Trust AI?—A Requirement Analysis for (Generative) AI-based Texts. InWirtschaftsinformatik 2023 Proceedings. 35 .
- Oberdorf, F., Schaschek, M., Weinzierl, S., Stein, N., Matzner, M., Flath, C. M., 2022. Predictive End-to-End Enterprise Process Network Monitoring. Business & Information Systems Engineering.
- Oberdorf, Felix; Schaschek, Myriam; Stein, Nikolai; and Flath, Christoph, "Neural Process Mining: Multi-Headed Predictive Process Analytics in Practice" (2021). ECIS 2021 Research Papers. 54.
- Oberdorf, Felix; Wolf, Peter; Schaschek, Myriam; and Stein, Nikolai, "Strategic Decision Support System for Fleet Investments in the Vaccine Supply Chain" (2021). ICIS 2021 Proceedings. 3.
