Charlotte Cambier van Nooten

PhD student, Data Science, Institute for Computing and Information Sciences, Radboud University Nijmegen, Radboud University

Joined

April 2026

Names

Charlotte Cambier van Nooten (Preferred)

Emails

****@ru.nl (Confirmed)

Personal Links

Career & Education History

PhD student

Data Science, Institute for Computing and Information Sciences, Radboud University Nijmegen, Radboud University (cs.ru.nl)

Present

Advisors, Relations & Conflicts

PhD Advisor

Yuliya Shapovalova

2022 – Present

PhD Advisor

2022 – Present

Expertise

Graph Neural Networks

Present

Graph Machine Learning

Present

Uncertainty Quantification

Present

Precipitation nowcasting

Present

Power grid reliability

Present

Publications

Endpoint Symmetry for Edge Updates: Weight-Space Redundancy in GNNs on Undirected Graphs
Charlotte Cambier van Nooten, Stijn van den Beemt, Yuliya Shapovalova, Tom Heskes
- ICML 2026 Workshop WSS Poster
- Readers: Everyone
Uncertainty Quantification Using GNN Deep Ensembles for Contingency Decisions in the MV‐Grid
Charlotte Cambier van Nooten, Tom van de Poll, Tom Heskes, Yuliya Shapovalova
- IET Generation, Transmission & Distribution
- Readers: Everyone
Graph neural networks for assessing the reliability of the medium-voltage grid
Charlotte Cambier van Nooten, Tom van de Poll, Sonja Füllhase, Jacco Heres, Tom Heskes, Yuliya Shapovalova
- Applied Energy
- Readers: Everyone
Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands
Charlotte Cambier van Nooten, Koert Schreurs, Jasper S. Wijnands, Hidde Leijnse, Maurice Schmeits, Kirien Whan, Yuliya Shapovalova
- Artificial Intelligence for the Earth Systems
- Readers: Everyone

Co-Authors