Michael Heider

Research Assistant
Lehrstuhl für Organic Computing
Phone: +49 821 598 69261
Email:
Room: 1031 (W)
Address: Am Technologiezentrum 8, 86159 Augsburg

Research foci

My main research is to automate parameter optimisation of industrial machinery by including existing expert knowledge into advanced machine learning algorithms. In our case study we try to implement our concepts for the case of additive manufacturing (colloquially referred to as 3D printing) using FDM machines. An important role in finding optimal parameter settings plays predicting the quality, that results from applying a given setting.

 

  • evolutionary rule-based learning (supervised and reinforcement learning)
  • unsupervised deep learning for feature extraction
  • 3D printing / additive manufacturing
  • adaptive systems

Publications

Michael Heider
2020 | 2019 | 2016

2020

Helena Stegherr, Michael Heider and Jörg Hähner. in press. Classifying metaheuristics: towards a unified multi-level classification system. DOI: 10.1007/s11047-020-09824-0
PDF | BibTeX | RIS | DOI

Richard Nordsieck, Michael Heider, Andreas Angerer and Jörg Hähner. 2020. Evaluating the effect of user-given guiding attention on the learning process. DOI: 10.1109/acsos49614.2020.00044
BibTeX | RIS | DOI

Michael Heider, David Pätzel and Jörg Hähner. 2020. SupRB: a supervised rule-based learning system for continuous problems.
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Michael Heider, David Pätzel and Jörg Hähner. 2020. Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations. DOI: 10.1145/3377929.3389963
BibTeX | RIS | DOI

2019

Michael Heider. 2019. Increasing reliability in FDM manufacturing. DOI: 10.18420/inf2019_ws52
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Richard Nordsieck, Michael Heider, Andreas Angerer and Jörg Hähner. 2019. Towards automated parameter optimisation of machinery by persisting expert knowledge. DOI: 10.5220/0007953204060413
PDF | BibTeX | RIS | DOI

2016

Sebastian von Mammen, Heiko Hamann and Michael Heider. 2016. Robot gardens: an augmented reality prototype for plant-robot biohybrid systems. DOI: 10.1145/2993369.2993400
BibTeX | RIS | DOI

Curriculum/Vitae

since 2019 Research Assistant with the chair for Organic Computing
2015–2018 Master programme Computer Science and Information-oriented Business Management at the University of Augsburg
2012–2016 Bachelor programme Computer Science at the University of Augsburg

Courses / teaching

(applied filters: semester: current | institute: Organic Computing | lecturers: Michael Heider | course types: all)

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