Schmidt

Wiss. Mitarbeiter/-in

M.Sc. Johann Schmidt

Institut für Intelligente Kooperierende Systeme (IKS)
AG Artificial Intelligence Lab
Universitätsplatz 2, Gebäude 29, 39106 Magdeburg, G29-028
About me

Education

  • 2014-2018 Bachelor Electrical Engineering, University of applied Science Magdeburg-Stendal, Germany
  • 2018-2020 Master Digital Engineering, Otto-von-Guericke University Magdeburg, Germany
  • since 2020: Researcher/PhD student at the AI Lab, OVGU

Main Research Interests

  • Combinatorical Optimization, eg. Deep TSP or scheduling solvers
  • Traffic prediction / forcasting and traffic light intersection optimization
  • Deep Reinforcement Learning
  • Geometric Deep Learning and Graph Neural Networks

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Publications

  • S. Lang, T. Reggelin, J. Schmidt, M. Müller, and A. Nahhas. NeuroEvolution of augmenting topologies for solving a two-stage hybrid flow shop scheduling problem: A comparison of different solution strategies. Expert Systems with Applications, 2021. [PDF]
  • J. Schmidt and S. Stober. Approaching Scheduling Problems via a Deep Hybrid Greedy Model and Supervised Learning. IFAC Symposium on Information Control Problems in Manufacturing, 2021. [PDF]

 

Last Modification: 13.01.2022 - Contact Person: Michael Preuss