The WUR Scientific Machine Learning Network

At Wageningen University and Research, different researchers are exploring the potential of SciML for their scientific domain. Examples of disciplines in which ScML is explored are crop growth modelling and food supply chains. More recently, hydrologists and soil scientists have started to use the novel SciML-technique. To bind forces, exchange experiences, and finally, advance the knowledge and use of SciML, we have created a cross-disciplinary network of WUR researchers interested in this topic.

We organise network meetings during which we go in-depth on SciML and we present our work at seminars and symposia to share our discoveries with a wider audience of non-specialists. The aim of the SciML network is to exchange experiences on SciML between researchers of Wageningen University & Research.

Within climate research and especially climate adaptation, models are used to predict system behaviour under different circumstances and scenarios. These models are often process-based. A limitation of these models is limited applicability in practice, especially when human interventions (adaptations) are simulated. On the other hand, machine learning techniques are too black-box because process-understanding is needed to properly upscale or extrapolate. Bringing together the best of both worlds helps to make better predictions. SciML brings these two techniques together in one framework that requires more understanding within WUR.

Project description

Our network contributes to increasing the understanding of SciML by opening up knowledge to a wider audience of researchers. Our project results will be:

  1. Quarterly SciML network meetings, open to those interested in researching SciML and using SciML in their research.
  2. Maintained website
  3. Cooperation with the Dutch joint NMDC modelling research centre
  4. Mini-symposium for a broad audience


SciML - WUR Scientific Machine Learning Network
One meetup held, one planned for June (see our website)