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"Behind the many buzzwords, a lot of in-depth conceptual work is required to promote digitalisation in education. Together with extensive research, also to avoid 'reinventing the wheel' (or the whitepaper), this is what I do at the iit."

Dr. Robert Rentzsch

rentzsch@iit-berlin.de
+49 (0)30 310078 - 5810

Focal areas of work

  • Digitalisation in education
  • Machine Learning, AI
  • Digital Credentials, Badges
  • Concepts for online information portals
  • Open (research) data
  • Data analysis and visualisation

Curriculum Vitae

Following his studies in Muenster and Cologne, specialising in bioinformatics and biochemistry, Robert Rentzsch did his PhD on the classification of protein domains based on sequence, structure and function at University College London. After returning to Germany, he joined the Robert Koch Institute in Berlin as a postdoctoral scholar, in what was then a relatively young bioinformatics group. Over the course of six years, his work focused, among other things, on algorithms for machine learning as well as the preparation and processing of data for their training and testing, arguably the most important part in practice. Concrete applications were the prediction of bacterial pathogenic phenotypes on the molecular (single proteins as virulence factors) as well as on the organismic (based on the whole genome) level. In early 2019, Dr Rentzsch moved from science to consulting and science funding, joining the iit within VDI/VDE-IT.

Publications

  • Rentzsch, Robert; Deneke, Carlus; Nitsche, Andreas; Renard, Bernhard Y. (2019): Predicting Bacterial Virulence Factors: evaluation of machine learning and negative data strategies. In: Briefings in Bioinformatics.
  • Bartoszewicz, Jakub M.; Seidel, Anja; Rentzsch, Robert; Renard, Bernhard Y. (2019):┬áDeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks. In: Bioinformatics, Vol. 36, Issue 1.

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