Scholar
Julie Keisler
Google Scholar ID: TWowILgAAAAJ
INRIA Paris
Citations & Impact
Citations
20
H-index
2
i10-index
0
Publications
11
Co-authors
3
list available
Publications
Resume (English only)
Academic Achievements
- Developed a Python package called DRAGON to optimize deep neural networks and, more recently, generalized additive models. The code is available on GitHub.
Research Experience
- Currently a researcher in the ARCHES team from INRIA Paris.
Education
- Completed PhD in January 2025 under the supervision of Claire Monteleoni (INRIA Paris and University of Colorado Boulder), El-Ghazali Talbi (INRIA Lille and Université de Lille), Margaux Brégère (EDF R&D and Sorbonne Université), Gilles Cabriel, and Sandra Claudel. The thesis is entitled 'Automated Deep Learning: algorithms and software for energy sustainability'.
Background
- Research interests include AI-driven methods for statistical downscaling, automated machine learning (particularly neural architecture search), and the use of AI for the energy transition in general.
