Chong You, Claire Donnat, Daniel P. Robinson, and René Vidal. "Large-Scale Subspace Clustering for Computer Vision."
- Classes Préparatoires in Mathematics and Physics (MPSI/ MP*) in Lycée Privé Sainte Geneviève, Versailles, 2010-2012
- Diplôme d’Ingénieur, Ecole Polytechnique, 2014
- M.S. in Applied Mathematics, Ecole Polytechnique, 2015
- Ph.D in Statistics, Stanford University, 2020 (expected)
- Winter 2016-Spring 2020: Teaching Assistant (CS229 (Machine Learning), STATS 60, 110, 191, 200, 216, 305A, 315B.)
- Stanford University, CA
- Responsibilities include preparing exams, homework assignments, holding office hours, leading recitation sessions and grading for classes of various sizes (from 60 to 220 students).
- Won one of the department’s best TA awards in Spring 2016 and a University Centennial award in Spring 2019.
- 06/2019-08/2019: HAIL Research Fellow in the AI team at Hudson River Trading
- New York, NY
- Fellowship in HRT’s AI Research Lab, focusing on using deep-learning techniques for time series and market structure analysis.
- 06/2018-09/2018: PhD Research Intern in Core Data Science at Facebook.
- Menlo Park, CA
- Summer research internship as part of the Core Data Science team at Facebook, working on graph classification to improve understanding of user groups’ dynamics.
- 06/2017-08/2017: Quantitative Analyst -Research Intern at G-Research.
- London, UK
- Summer research internship as a Quantitative Research Analyst Intern at G-Research, Europe’s largest quantitative hedge fund, which leverages tools from statistics and machine learning to analyze financial datasets .
- Proficient User: Python, Pytorch, R
- Working Knowledge: Java, Tensorflow, C++
Donnat, Claire and Holmes, Susan (2018). "Tracking network distances: an overview." Annals of Applied Statistics 12.2 (2018): 971-1012.
Donnat, Claire. (2018). "Learning Structural Node Embeddings Via Diffusion Wavelets."
Miolane, Nina et al. (2018). "Geomstats: a Python Package for Riemannian Geometry in Machine Learning." arXiv.
Donnat, Claire and Holmes, Susan. (2019). "Convex Hierarchical Clustering for Graph-Structured Data." IEEE Transactions on Signal Processing.
Claire Donnat, Leonardo Tozzi and Susan Holmes (2019). "Constrained Bayesian ICA for Brain Connectomics 1." arXiv.
Poster at 2nd Graph Signal Processing Workshop, Carneggie Mellon University, Pittsburgh, OH
Poster at CAT symposium, Stanford University, Stanford, CA
Workshop Talk at 3rd Graph Signal Processing, École Polytechnique Fédérate de Lausanne, Lausanne, Switzerland
Workshop Talk at 4th Graph Signal Processing Workshop, University of Minnesota, Minneapolis, MN
Conference Proceedings Talk at Asilomar Conference of Signals, Systems and Computers, Pacific Grove, CA