Paris, Île-de-France, France
I am a research scientist in AI with passion for biological systems. I have extensive experience in data science, MLand software engineering, signal processing, computational modelling and developing AI agents for biotechnology. I am also a Pyladies Paris co-organizer and contributor to open source such as scikit-learn or PyDeseq2. My experience varies from wet lab neuroscience-related experiments, computation and modelling to data science ML and AI: - Artificial Intelligence & Machine Learning - Data Science & Statistical Analysis - Computational Neuroscience & Neuroimaging - Large-scale Clinical & Imaging Data Analysis (MRI, EEG and ECG, biomedical data) - Python, Scientific Computing - Computer Vision & Signal Processing - Federated Learning & Multi-partner Projects - Research Project Coordination & Collaboration - Scientific Writing & Publications - Open Source Development & Community Engagement (eg, Scikit-Learn, Pydeseq2 contributor, Pyladies Paris organizer)
- AI engineering Developing internal agentic capabilities - Data Science Working on projects with pharma partners: - Melloddy: large multi-partner federated learning based project - Projects with timeseries data and spatial transcriptomics - Software and Machine Learning Engineering Developing open source libraries (PyDeseq2, Flamby, Substra)
coauthor and contributor of: - PyDeseq2: Python implementation of deseq2: differential expression analysis (DEA) with bulk RNA-seq data - FLamby: Benchmark for cross-silo federated learning
federated learning | software engineering
Co-lead of the PyLadies Paris chapter. We organize meetups, workshops conferences and networking activites for women interested in the Python programming language. - Co-organized events with other communities abroad - Selected to join the "Python Software Foundation Meetup Pro Network" in June 2021
Software Development | Machine Learning | Data Science working with Gaël Varoquaux and Alexandre Gramfort o Contributed to Scikit-Learn o Coordinated data science research projects, eg: - Segmentation of medical images deep learning algorithms - Source localization of brain signals (MEG and EEG recordings) o Developing RAMP platform for running ML challenges o Built connections with external partners
Computational Modeling | Systems Neuroscience | Signal processing in the group of Alain Destexhe Developed a model of brain activity and analyzed it's signal with a correspondence to relevant biological processes. o Published 2 articles in peer-reviewed journals (with reproducible Docker images) o Presented at 10+ coferences.
Brain Computer Interface | Machine Learning in the group of Klaus Robert Müller Developed BCI application to facilitate communication with locked in patients: o Designed, programmed and tested a feedback loop between the computer and the subject using EEG and eyetracker. Signal was being processed in real time to feed classifier results back to the system.