13 Apr 2021 - 2 min

The magic of machine learning: call winners announced

A small-scale initiative, this call for proposals supports researchers who expect to benefit from machine learning or deep learning, but who need additional expertise in applying these methods. The winners are awarded with a week-long workshop followed by several months of consultancy by a dedicated team of our Research Software Engineers.

Following an extensive selection and deliberation process, the eScience Center is pleased to announce the following winning projects in their respective categories:

Physical Sciences and Engineering
  1. “Machine Learning for the complex response of the Wadden Sea,” by M. Duran Matute (TUe)
  2. “Looking through: Finding the hidden structure in glassy systems,” by Liesbeth M. C. Janssen (TUe)
  3. “Opportunistic Sensing of Hydrometeors with Commercial Microwave Links,” by Gert-Jan Steeneveld (WUR)
Life Sciences
  1. “Automated video-based movement assessment using machine learning to support personalized treatment of movement disorders,” by Helga Haberfehlner (UMC/VU)
  2. “Predicting the Brugada ECG without ajmaline,” by Elisabeth Lodder (Amsterdam UMC)
  3. “Deep learning for accelerated scatter correction in quantitative PET/MRI,” by W.J. Branderhorst (UMC Utrecht)
  4. “Rethinking risk of falls in stroke survivors using machine learning approaches,” by Sina David (VU)
  5. “Epigenetic signatures for complex diseases,” by Peter Henneman (Amsterdam UMC)
Social Sciences and Humanities
  1. “Morphological Parser for Inflectional Languages Using Deep Learning,” by Wido van Peursen (VU)
  2. “Different kinds of laughter: A machine learning approach,” by Disa Sauter (UVA)
  3. “Automation of the cognitive mapping text-analysis technique,” by Femke van Esch (UU)
  4. “Recognising symbolism in Turkish television drama,” by Peter Verhaar (Leiden Univ)

The team at eScience Center congratulates all winners, and thanks all participants for the variety and diversity of strong submissions. Together with our extended research community, we look forward to the results of these projects in due course.