Hans Weytjens is a postdoc researcher. His current research interests include prescriptive process monitoring, generativeAI, the autonomous enterprise and RAGops.
Hans holds a M.Sc. Business and Information Science from the KU Leuven, an MBA Finance from the University of Chicago, and a Ph.D. in machine learning for predictive and prescriptive process monitoring from the KU Leuven.
Curriculum Vitae
Professional Experiences
| Since 10/2023 | Post-Doc | Technische Universität München |
| Since 10/2023 | Guest Professor | KU Leuven, Belgium |
| Since 12/2000 | Freelancer Strategy Consulting & Management | |
| 01/2018 - 06/2028 | Freelancer Machine Learning | Unite |
| 10/2002 - 12/2016 | Owner | WSW International GmbH |
| 07/2000 - 02/2002 | CFO | advanced commerce AG |
| 1996 - 2000 | Project Manager | Roland Berger Strategy Consultants |
| 03/1994 - 02/1996 | Derivatives Trader | ING AG |
Education
| 2019 - 06/2023 | PdD Candidate | KU Leuven, Belgium |
| 1990 - 1991 | Master of Business Administration (MBA) | The University of Chicago Booth School of Business, USA |
| 1986 - 1990 | KU Leuven, Belgium |
Publications
Wuyts, Bart, Weytjens, Hannes, vanden Broucke, Seppe, and De Weerdt, Jochen. "The DyLoPro Library: Comprehensively Profiling the Dynamics of Event Logs by Means of Visual Analytics." 2023.
Weytjens, Hannes, Verbeke, Wouter, and De Weerdt, Jochen. "Timing Process Interventions with Causal Inference and Reinforcement Learning." arXiv preprint arXiv:2306.04299, 2023.
Wuyts, Bart, Weytjens, Hannes, vanden Broucke, Seppe, and De Weerdt, Jochen. "Dylopro: Profiling the dynamics of event logs." International Conference on Business Process Management. Cham: Springer Nature Switzerland, 2023, 146–162.
Weytjens, Hannes, Verbeke, Wouter, and De Weerdt, Jochen. "Timed Process Interventions: Causal Inference vs. Reinforcement Learning." International Conference on Business Process Management. Cham: Springer Nature Switzerland, 2023, 245–258.
Weytjens, Hannes. Machine Learning for Predictive and Prescriptive Process Monitoring. 2023.
Baesens, Bart, Verbeke, Wouter, De Smedt, Johannes, De Weerdt, Jochen, and Weytjens, Hannes. Pattern and Anomaly Discovery in Data. 2023.
Baesens, Bart, Verbeke, Wouter, De Smedt, Johannes, De Weerdt, Jochen, and Weytjens, Hannes. Data Preprocessing and Feature Engineering. 2023.
Weytjens, Hannes, and De Weerdt, Jochen. "Learning uncertainty with artificial neural networks for predictive process monitoring." Applied Soft Computing 125 (2022): 109134.
Weytjens, Hannes, and De Weerdt, Jochen. "Learning uncertainty with artificial neural networks for improved remaining time prediction of business processes." International Conference on Business Process Management. Cham: Springer Nature Switzerland, 2021, 141–157.
Weytjens, Hannes, and De Weerdt, Jochen. "Creating unbiased public benchmark datasets with data leakage prevention for predictive process monitoring." International Conference on Business Process Management. Cham: Springer Nature Switzerland, 2021, 18–29.
Weytjens, Hannes, Lohmann, Enrico, and Kleinsteuber, Martin. "Cash flow prediction: MLP and LSTM compared to ARIMA and Prophet." Electronic Commerce Research 21, no. 2 (2021): 371–391.
Weytjens, Hannes, and De Weerdt, Jochen. "Process outcome prediction: CNN vs. LSTM (with attention)." Business Process Management Workshops: BPM 2020 International Workshops. Cham: Springer Nature Switzerland, 2020, 77–88