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Workshop on "Deep Learning" – definition and application to process industry

The DYN group hosted a deep learning workshop on 02.03.2020, where several PhD students of the biochemical and chemical engineering faculty of the TU Dortmund along with guest speakers from different industries exchanged the outcome of their works on the relevant topics.


In the scope of the PhD workshop “Deep Learning – What is deep learning and how can it be applied to the process industry”, several PhD students of the biochemical and chemical engineering faculty prepared talks to introduce their work with deep learning/machine learning/artificial intelligence methods. As a guest, Dr.-Ing. Fabian Bürger from the automotive corporation, Valeo [1,2] attended the workshop. Dr.-Ing. Bürger received his PhD degree in the area of automatic optimization for machine learning methods. The talks led to several interdisciplinary discussions between visitors of the faculties statistics, finance, logistics, sports, computer science and biochemical and chemical engineering.


  • Fabian Bürger - What is deep learning and its application to autonomous driving
  • Matthias Rodeck - Characterization of sprays by image recognition with neural networks
  • Janine Lins - Particle characterization during crystallization using CNNs
  • Corina Nentwich - When data is expensive: Adaptive Sampling for the training of surrogate models
  • Fabian Bürger - How to apply deep learning to other fields than image recognition
  • Tim Janus - Surrogate-assisted flowsheet optimization for steady-state models
  • Kai Kruber - Optimization of intensified distillation columns with machine learning methods
  • Pourya Azadi - Saving energy in a blast furnace by application of neural networks

Contact and slides:

Slides will be provided on request. Feel free to contact the speakers directly or write an email to the organization (here).

[1] https://www.valeo.com/en/comfort-driving-assistance-systems/

[2] http://www.is.uni-due.de/lehrstuhl/mitarbeiter/fabian_buerger/