Johannes Roider
Johannes Roider, M. Sc.
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik
Carl-Thiersch-Straße 2b
91052 Erlangen
- Email: johannes.roider@fau.de
| Since 06/2021 | Researcher and PhD Candidate
Machine Learning and Data Analytics Lab |
| 04/2018 – 05/2021 | M. Sc. Computer Science
Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Germany Working student at Siemens Healthineers (04/2020 – 04/2021) Working student at Siemens AG (04/2019 – 03/2020) Working student at 8select GmbH (04/2018 – 04/2021) |
| 10/2015 – 03/2018 | B. Sc. Business Information Systems
University of Regensburg, Germany Working student at 8select GmbH (03/2016 – 03/2018) |
| 10/2014 – 10/2015 | Internship
Jebsen Industrial Technology Co. Ltd., Hong Kong |
| 09/2013 – 07/2014 | Erasmus student
University of Padova, Italy |
| 10/2011 – 09/2014 | B. Sc. European Economic Studies
Otto-Friedrich University Bamberg, Germany Student Assistant at Ingolstadt University of Applied Sciences (03/2012 – 10/2012) |
In my research I focus on Process Mining related questions, mainly in the field of Predictive Process Monitoring. I pursue my research together with Siemens Healthineers Customer Services in the project Holistic customer-oriented service optimization for fleet availability.
2024
- , , , :
Assessing the Performance of Remaining Time Prediction Methods for Business Processes
In: IEEE Access (2024), p. 1-19
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3459648
URL: https://ieeexplore.ieee.org/abstract/document/10679137
BibTeX: Download - , , :
Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring
BPM: International Conference on Business Process Management (Krakow, 1. September 2024 - 6. September 2024)
In: Andrea Marrella, Manuel Resinas, Mieke Jans, Michael Rosemann (ed.): Business Process Management, 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Proceedings, Cham: 2024
DOI: 10.1007/978-3-031-70396-6
URL: https://link.springer.com/book/10.1007/978-3-031-70396-6
BibTeX: Download
| Winter 2023/24 | Seminar Machine Learning and Data Analytics for Industry 4.0 |
| Summer 2023 | Seminar Machine Learning and Data Analytics for Industry 4.0 |
| Winter 2022/23 | Seminar Machine Learning and Data Analytics for Industry 4.0
Project Machine Learning for Time Series |
| Summer 2022 | Seminar Machine Learning and Data Analytics for Industry 4.0 |
| Winter 2021/22 | Seminar Machine Learning and Data Analytics for Industry 4.0
Project Machine Learning for Time Series |
| Year | Name | Title |
| 2024 | Osman Yigit | Designing a Framework for Concept Drift Handling in Predictive Process Monitoring (Master’s Project) |
| 2023 | Hana Ibrahim | Implementing an Optimized Algorithm for Local Process Mining with Java (Master’s Project) |
| 2023 | Issa Issa | A Distributed Python Implementation for HPC Local Process Mining (Master’s Project) |
| 2022/2023 | Weixin Wang | Evaluating Remaining Time Prediction of Business Processes with Event Log Imperfections Using Synthetic Event Log Data (Master’s Thesis) |
| 2022/2023 | Hung Nguyen | Neural Temporal Point Processes for Predictive Process Monitoring (Master’s Project) |
| 2022 | Chirag Pandav | Evaluating and Optimizing a Predictive Process Monitoring Package for Scalability (Master’s Project) |
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