David Wittenberg

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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

  1. Research Interests
  2. Teaching
  3. CV
  4. Publications
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Research Interests

  • Machine learning, in particular Artificial Neural Networks
  • Estimation of Distribution Algorithms
  • Genetic Programming
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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
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CV

  • Since 07/2018
 Research Assistant and Doctoral Candidate at the Chair of Information Systems and Business Administration, Prof. Dr. Franz Rothlauf
  • 10/2015 - 05/2018
 Master of Science in Management (Johannes Gutenberg University Mainz)
  • 01/2017 - 04/2017
 Internship Supply Chain Management (BASF Ludwigshafen)
  • 09/2016 - 12/2016
 Supporting a coffee startup in Nicaragua (Engagement Global gGmbh, ASA programme)
  • 04/2012 - 07/2015
 Bachelor of Science in Economics (Johannes Gutenberg University Mainz) & Licence mention Sciences de Gestion (Université Paris X), Franco-German Double-Degree
  • 03/2014 - 06/2014
 Internship Human Resources (Audi Brussels SA/NV)
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Publications

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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
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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
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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
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