Department of Statistics and the College
Claire Donnat’s current research focuses on the statistical analysis of graphs and networks, particularly in view of applying these methods to biomedical data. She is especially interested in neuroscience and brain connectomics applications. She has also developed statistical and machine learning methods for graph-structured data, with a special focus on topics such as graph signal processing and geometric deep learning
Her work has been published in the Proceedings of the IEEE Asilomar Conference, Annals of Applied Statistics, arXiv, and other journals.
Donnat earned her BSc and MSc in applied mathematics and computer science at École Polytechnique, and received her PhD in statistics from Stanford University. Previously, she held a research fellowship in artificial intelligence at Hudson River Trading, where she used deep learning techniques for time series and market structure analysis.