Analytics
- Flavio Hafner (current)
- Johan Hidding
We rotate the leadership, and the current lead is indicated with (current)
.
The mission of this SIG in the broadest sense, is to raise general knowledge on applied analytical and numerical solutions in the Netherlands eScience Center, as well as their technical implementations. We aim for a deeper understanding than is generally needed to use a specific method, that is, to go beyond the black-box level of thinking. Mathematics/statistics is capable of drastically reducing the complexity of existing solutions in a wide variety of cases, as well as formulating novel ideas that lie outside our comfort zone.
https://github.com/nlesc-sigs/analytics-sig
Our interest lies in the following themes:
- statistical computing for social sciences
- causal inference and machine learning
- recent developments in techniques for data sharing through federated learning and differential privacy
- understanding deep learning algorithms and backpropagation
- simulation modeling of the socio-economic aspects of climate change
For some of these topics, we will collaborate with the Machine Learning SIG.
- Internal training on a specific topic (mentioned above)
- Sharing knowledge on statistics (at basic/intermediate level)
- Transfer of knowledge by inviting external speakers
- Keeping a portfolio of expertise in analytics at the center
- Making a collection of tools and resources