Contact
Universitätsstraße 38
70569 Stuttgart
Germany
Room: 2.365
Office Hours
On appointment
Subject
Working Area: Machine Learning, Ensemble Learning, Classification
In my PhD topic " Deployment and data-driven fusion of heterogeneous predictive models" I deal with the creation of optimized ensembles, i.e. the combination of multiple classification models. For this purpose, the influence of data, model diversity, etc. on ensembles shall be investigated. Furthermore, an automated procedure shall be developed to create optimized ensembles based on the discovered connections.
Citation Metrics
- Google Scholar: Profile
- ORCID: 0000-0003-4808-1922
- Research Gate: Profile
Publications
2023
Julius Voggesberger. "Optimierung von Klassifikator-Ensembles mit AutoML". In: GvDB. 2023.
Julius Voggesberger, Peter Reimann und Bernhard Mitschang. “Towards the Automatic Creation of Optimized Classifier Ensembles”. In: Proc. of the 25th Int. Conference on Enterprise Information Systems (ICEIS) – Volume 1. 2023, S. 614–621.
Michael Behringer, Dennis Treder-Tschechlov, Julius Voggesberger, Pascal Hirmer und Bernhard Mitschang u. a. “SDRank: A Deep Learning Approach for Similarity Ranking of Data Sources to Support User-Centric Data Analysis”. In: Proc. of the 25th Int. Conference on Enterprise Information Systems (ICEIS) – Volume 1. 2023, S. 419–428.
Thesis
J. Voggesberger, "AutoML für Ensembles: Erhöhung der Klassifikationsperformanz durch Optimierung der Modelldiversität und der Entscheidungsfusion"
Masterthesis. 2022.
J. Voggesberger, " Evaluation von Zwischenergebnissen in Entscheidungsbäumen"
Bachelorthesis. 2019.
Summer Term 2025
- Seminar "Vertiefungsthemen von Data Science"
Organisation and Supervision
Winter Term 2024/2025
- Lecture Exercise "Datenbanken und Informationssysteme"
Übungsleiter
Summer Term 2024
- Advanced Seminar "Data Management for End-to-End Machine Learning"
Organisation and Supervision
Winter Term 2023/2024
- Advanced Seminar "Advanced Topics in Data Management"
Organisation and Supervision - Lecture Exercise "Datenbanken und Informationssysteme"
Übungsleiter - Pracitcal Course "Automated Machine Learning for Classification Ensembles"
Supervision
Summer Term 2023
- Advanced Seminar "Data Management for End-to-End Machine Learning"
Organisation and Supervision
Winter Term 2022/2023
- Seminar "Entwicklung von Data-Science-Anwendungen"
Supervision
Student Projects in Progress
- Master Thesis: Meta-Learning for Ensembles using Latent Space Representations
- Bachelor Thesis: Comparison of Approaches for the Automated Selection of the Classifier Number in Heterogeneous
