About Axel
Data scientist et expert en IA pour l'aide à la décision dans les environnements de santé réglementés. Mon expérience combine la recherche universitaire, l’industrie deeptech et l’entrepreneuriat agile pour développer des solutions d'IA robustes, traçables et conformes : de la preuve de concept au déploiement clinique. J’ai collaboré avec des cliniciens, des
ingénieurs et des experts réglementaires pour transformer les données brutes en décisions cliniques éclairées. Basé à Grenoble (France), j'envisage des missions en régions Rhône-Alpes et Côte d'Azur.
Central Atlas Tamazight
Native or bilingual
English
Fluent
French
Native or bilingual
Spanish
Basic
Can work on-site
Grenoble (up to 30km), Lyon (up to 30km), Annecy (up to 30km), Chambéry (up to 30km), Valence (up to 30km)
Experience
- IcadomConsultant GenAI pour secteur réglementé : Recherche CliniqueMEDICALMarch 2025 - June 2025 (3 months)Grenoble, FranceCRO specialized in clinical investigation and medical device evaluation.Project Goal: Design of a multi-functional AI assistant automating the processing of regulatory and clinicaldocumentation under EU MDR, ISO 14155, and GDPR.Main achievements:• Built a retrieval-augmented generation (RAG) enabling clinical teams to query regulatory content with LLMs.• Automated document templates and prefilled forms for study management.• Developed the full backend in Python / LangChain / Faiss DB / FastAPI, deployed via Docker on OVH Cloud.• Integrated a Flutter mobile and web interface for clinical and business users.• Implemented MLOps tracking via MLflow and version control through GitHub.• Reduced document search time by >70% and achieved Recall@5 >85%, Precision@5 >90%.Soft skills: autonomy, pedagogical approach, documentation rigor, stakeholder communication.
- Blue-OrthoAI Expert – Computer-Assisted Orthopedic SurgeryMEDICALSeptember 2021 - February 2025 (3 years and 5 months)Grenoble, FranceSubsidiary of Exactech (USA), developing navigation systems and surgical planning software.Mission: Develop and deploy AI pipelines for 3D bone segmentation, landmark detection, and surgical navigation.Key contributions:• Designed CNN-based segmentation algorithms for shoulder and hip CT scans (Dice = 98%).• Reduced pre-operative image processing time by 75% compared to semi-automatic methods.• Managed datasets of 58,000+ CT exams with multi-protocol normalization.• Collaborated with surgeons, QA engineers, and SW developers in a regulated ISO 13485/MDR environment.• Contributed to 4+ scientific publications and received the 2nd Prize at CAOS 2024.• Integrated AI models into C++ production pipelines and Azure Cloud.Soft skills: clear communication with clinicians, quality documentation, cross-functional teamwork.
- GipsaResearch Associate in Computer Vision & Deep LearningRESEARCHJune 2017 - August 2021 (4 years and 2 months)Grenoble, FranceAcademic research (PhD and ATER contract) on vehicle segmentation and tracking in spatio-temporal video streamsusing GPU-accelerated architectures.Key results:• Designed hybrid GMM and CNNs for object detection and tracking on embedded GPU systems.• Achieved 4× improvement in inference speed with optimized CUDA pipelines.• Published 4 peer-reviewed papers and presented at international conferences.• Conducted reproducible experiments and developed a GPU optimization guide for video analysis.Technical stack: Python, PyTorch, OpenCV, CUDA, C/C++, Git, Linux HPC.
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Education
- PhDGrenoble Alpes University2020