Clémence Réda
Researcher at CNRS, Institut de Biologie de l'Ecole Normale Supérieure
Paris, Ile-de-France
Summary
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Senior🎓
Top SchoolClémence Réda is a researcher with nine years' experience at the intersection of machine learning, networks and genomics, currently leading multimodal drug-effect studies at CNRS/IBENS. Her PhD and postdoctoral work pioneered the use of gene regulatory networks and multi-armed bandit recommender systems for sample-efficient drug repurposing, with publications at AISTATS, NeurIPS and CMSB. She has introduced methods to automatically build disease-specific regulatory networks and to detect master regulators, and extended regulatory models to include non-coding elements to improve interpretability. During a Marie Skłodowska-Curie fellowship she adapted collaborative filtering to drug discovery and delivered interpretable drug–disease association algorithms now published in high-impact outlets. Comfortable in interdisciplinary teams, she combines formal training in mathematics, computer science and genetics with hands-on implementation of pipelines and web tools. An understated strength is her knack for translating theoretical constraints in regulatory dynamics into practical, experimentally-relevant predictors of drug efficacy.
9 years of coding experience
Master's degree, Mathematics, Master's degree, Mathematics at École normale supérieure Paris-SaclayDoctor of Science, Genetics, Doctor of Science, Genetics at Université Paris Cité
Github Skills (11)
bioinformatics10
conda10
package-management10
bioconda9
journal7
open-access7
academia6
python6
creative-commons5
algorithms5
algorithm5
Programming languages (3)
Github contributions (5)
clreda/NORDic
Nov 2022 - Jan 2023
Network-Oriented Repurposing of Drugs Python Package
Contributions:15 releases, 5 commits, 2 PRs in 2 months
bandit-algorithmboolean-networkdrug-repurposingdrug-simulationgene-regulatory-network
clreda/clreda.github.io
Aug 2018 - Mar 2025
Contributions:1 PR, 135 pushes, 1 branch in 6 years 8 months
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