Room: Phone: Fax: Mail: Office hours: |
01/263 (ReWi I) +49 6131 39 - 27556 +49 6131 39 - 22185 wittenberg@uni-mainz.de Tuesday, 11:00 a.m. - 12:00 p.m. |
Contents
Research Interests
- Machine learning, in particular Artificial Neural Networks
- Estimation of Distribution Algorithms
- Genetic Programming
Teaching
- Lecturer of the preparation course for the SAP S/4HANA consultant certification (September/October 2020)
- Tutor for the lecture "Computational Intelligence" - ST 2019, ST 2020
- Coordinate the tutorial for the lecture "Introduction to IT" - WT 2019/20, WT 2020/21
- Coordinate the tutorial for the lecture "Web technologies and E-Business" - WT 2018/19, WT 2019/20
- Supervise Bachelor and Master theses as well as Bachelor and Master seminar work- since WT 2018/19
- Tutor for the lecture "Mathematics" – WT 2017/18
CV
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Research Assistant and Doctoral Candidate at the Chair of Information Systems and Business Administration, Prof. Dr. Franz Rothlauf |
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Master of Science in Management (Johannes Gutenberg University Mainz) |
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Internship Supply Chain Management (BASF Ludwigshafen) |
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Supporting a coffee startup in Nicaragua (Engagement Global gGmbh, ASA programme) |
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Bachelor of Science in Economics (Johannes Gutenberg University Mainz) & Licence mention Sciences de Gestion (Université Paris X), Franco-German Double-Degree |
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Internship Human Resources (Audi Brussels SA/NV) |
Publications
2022
Wittenberg, D. (2022). Using Denoising Autoencoder Genetic Programming to Control Exploration and Exploitation in Search. In Lecture Notes in Computer Science (pp. 102-117). Springer International Publishing. DOI
2021
Olmscheid, C., Wittenberg, D., Sobania, D., & Rothlauf, F. (2021). Improving Estimation of Distribution Genetic Programming with Novelty Initialization. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 261-262. DOI
Schweim, D., Wittenberg, D., & Rothlauf, F. (2021). On sampling error in evolutionary algorithms. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 43-44. DOI
Schweim, D., Wittenberg, D., & Rothlauf, F. (2021). On sampling error in genetic programming. Natural Computing. DOI
2020
Wittenberg, D., Rothlauf, F., & Schweim, D. (2020). DAE-GP: denoising autoencoder LSTM networks as probabilistic models in estimation of distribution genetic programming. Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 1037-1045. DOI