Daniel Probst

Computer Science × Natural Sciences

Bio

I received my BSc in computer science at the Bern University of Applied Sciences in 2013 and my MSc in Bioinformatics and Computational Biology at the University of Bern in 2016. In 2020 I received my PhD in Chemistry and Molecular Sciences for my thesis “Scalable Methods for the Exploration and Visualization of Large Chemical Spaces” from the University of Bern under the supervision of Prof. Jean-Louis Reymond.

My main research interest is efficient machine learning and data visualisation applied to natural sciences, focusing on the intersection of chemistry and biology.

After a two-year stay as a permanent research staff member at IBM Research in the Team of Teodoro Laino working on machine learning for biocatalysis, I started as a postdoctoral researcher in the group of Prof. Pierre Vandergheynst at EPFL.

Publications

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Awards & Honours

  • 2022 Sandmeyer Award of the Swiss Chemical Society for the "important scientific breakthrough in the digitalization of synthetic organic chemistry that helps to improve digital workflows with state-of-the-art machine learning technologies." as part of the RXN for Chemistry project team.
  • 2021 Faculty Award of the Faculty of Science at the University of Bern for the dissertation “Scalable Methods for the Exploration and Visualization of Large Chemical Spaces”.
  • 2013. Graduated top of the year from Bern University of Applied Sciences.
  • 2009. Best practical thesis (Federal VET diploma in information technology) nationwide.