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NLeSc Analytics Special Interest Group (SIG)

The mission of this SIG is to raise general knowledge on applied analytical 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.

We meet roughly every 4 weeks and have, in between, also shared sessions with with Machine Learning SIG.

If you would like to present or invite an external speaker, please feel free to subscribe for any of the upcoming sessions in the table below using a pull request or by opening an issue.

Contact persons

Current schedule (2024)

Date Type Speaker Topic
January 25, 2024 Analytics/ML Laurent Soucasse Analysis and modelling of thermal convection from simulation data through machine learning techniques
March 14, 2024 Analytics Video: 3b1b But what is a convolution?
May 16, 2024 Analytics/ML Djura Smits Privacy protection I: federated learning
June 6, 2024 Analytics Flavio Hafner Privacy protection II: differential privacy
June 13, 2024 Analytics/ML Malte Lueken Introduction to amortized Bayesian inference
July 4, 2024 Analytics Nishant Joshi (Donders Institute) Methods for Comparing Unsupervised Clusters Across Modalities in a Single Neuron Dataset
September 12, 2024 Analytics/ML Video: Jake Hofman Prediction and explanation in the social sciences
October 3, 2024 Analytics -- --
October 10, 2024 Analytics/ML Bob Carpenter (Flatiron Institute) PPL design for Bayesian workflow
October 31, 2024 Analytics -- --
November 7, 2024 Analytics/ML -- --
November 28, 2024 Analytics Erik van Zwet (Leiden UMC) A new look at clinical trials
December 5, 2024 Analytics/ML -- --

Bring your own analytical challenges

Do you encounter statistics/mathematics problems in your projects? You can bring your issue to the SIG -- we can look at the issue together and do our best to find an applied analytical solution.

What do you need?

  • Open an issue on GitHub and label it Help | Title.
  • Describe the type of issue you want to address. Make sure to include:
    • What is the final goal?
    • What is the challenge?
    • A sample of your code (if possible).

We will discuss your issue during the next SIG meeting.

Share your statistics/mathematics solutions

Did you do something really cool? Share your experiences with the SIG! Contact the SIG to arrange a presentation in one of the upcoming sessions.

Previous sessions

2023 sessions

Date Type Speaker Topic
September 14, 2023 Analytics Video: Larry Wasserman Foundations of Statistical Inference
September 21, 2023 Analytics/ML Malte Lueken/Flavio Hafner Causal Inference
October 12, 2023 Analytics Thijs Vroegh Social network analysis: the aspect of time
October 19, 2023 Analytics/ML Video: Kyle Cranmer Simulation-based inference, interpretability, and experimental design
December 7, 2023 Analytics Chang Sun (Maastricht University) Differentially private synthetic data

Pre-2023

Date Topic Presenter
2018-04-12 Importance weighting Wouter
2018-05-07 Network formation models Laurens
2018-05-31 Network community detection Dafne
2018-06-21 Topological data analysis Johan
2018-08-02 Applied multilevel regression analysis Vincent
2018-11-05 Causal inference Mees
2019-01-21 Surrogate modelling Laurens
2019-07-18 Copula Sarah
2020-02-17 Uncertainty quantification Anna
2020-05-11 Complex systems Johan
2020-05-25 Confidence intervals Hanno
2020-06-08 Community detection Dafne
2020-06-22 Change detection in time series Wanda
2020-07-06 Chapter0-Introduction in "A First Course in Network Science" course
2020-07-20 Chapter1-Network elements in "A First Course in Network Science" course
2020-08-31 Chapter1-Network elements in "A First Course in Network Science" course
2020-09-14 Chapter1-Network elements in "A First Course in Network Science" course
2020-09-28 Chapter2-Small Worlds in "A First Course in Network Science" course
2020-10-12 Complex numbers for research software engineers Pablo R.
2020-10-26 Chapter2-Small Worlds in "A First Course in Network Science" course
2020-11-09 Voronoi diagrams and their many and varied uses, an introduction Johan
2020-11-23 Chapter2-Small Worlds in "A First Course in Network Science" Sarah
2020-12-07 Extreme value theory in weather & climate Gijs
2021-02-15 Chapter3-Hubs in "A First Course in Network Science" Dafne & Djura
2021-03-01 Random walks - part I video-lecture
2021-03-15 Chapter4-Directions in "A First Course in Network Science" Sarah & Barbara
2021-03-25 SIG lightning talk Pablo R.
2021-03-29 Mining gold with Bayesian Optimization Floris
2021-04-12 Chapter4&5- "A First Course in Network Science" Cunliang & Sarah
2021-04-26 Probability, by Richard Feynman Pablo R.
2021-06-07 Chapter6- "A First Course in Network Science" Cunliang & Sarah
2021-06-21 Brainstorming on applied mathematics Jens
2021-10-11 Optimization and Julia Abel
2021-11-08 Descriptive and Inferential statistics Study Group
2021-11-22 Brainstorming on applied mathematics Johan & Pablo
2022-01-17 Descriptive and Inferential statistics Study Group
2021-01-31 Pattern formation Frits
2022-02-28 Leaders meeting SIG meetings
2022-03-14 Study group Study Group
2022-03-28 Cancelled Cancelled
2022-04-11 Study group Study Group
2022-04-25 Study group Johan
2022-05-09 Brainstorm public SIGs Pablo R.
2022-07-18 SIG future strategy Pablo R.
2023-05-25 Geometric Numerical Integration and Scientific Machine Learning Michael Kraus, MPI - NMPP

Engineers with technical experience

Technique Engineer(s)
Structural Equation Modelling (SEM) Laurens
Hamiltonian Monte Carlo (HMC) Patrick
Applied dynamical systems theory Pablo R.
Computer vision Pablo R.
Geo-statistics Sarah

Engineers with software experience

Software Engineer(s)
R Laurens, Vincent, Pablo R.
SPSS Laurens
AMOS Laurens
Matlab Pablo R.

Potential topics

Topic Suggested by
Trade-off between stability and accuracy in deep learning Sarah
Kinematics with a smartphone Pablo R.
Something about partial differential equations? Pablo R.
Watch lecture on Network epidemiology Dafne
Watch lectures on Random walks Dafne
Course on Agent based models Dafne
Counter-intuitive probability problems Pablo R. and Barbara
Structure-preserving numerical methods for PDEs Artur
Reproducing a model Pablo R.

Potential invited speakers

Name Institution Expertise Notes
Pablo Deleteme NLeSC Making tables Delete this line

Interesting events

Location Organisation Event
Utrecht Utrecht University Data Science SIG
Utrecht Utrecht University R Cafe
Utrecht Utrecht University Complexity lab
Amsterdam MeetUp Data Science Amsterdam
Amsterdam MeetUp Amste-R-dam
- Congress Nederlands Matematisch Congres

Interesting training courses

Location Date Course
Utrecht 10 July 2019 - 12 July 2019 Introduction to Multilevel Analysis
Utrecht 15 July 2019 - 17 July 2019 Advanced Multilevel Analysis
Utrecht 19 August 2019 - 23 August 2019 Modeling the dynamics of intensive longitudinal data
Utrecht 15 April 2019 - 18 April 2019 Applied Bayesian Statistics
Utrecht 08 July 2019 - 12 July 2019 Introduction to Structural Equation Modeling using Mplus
Utrecht 15 July 2019 - 19 July 2019 Advanced course on using Mplus

Interesting open-source software

Software Topic and source
FORCE Mass-processing of selected medium-resolution satellite image archives

Other resources