Applied Deep Learning engineer specializing in Computer Vision for medical imaging, designing AI systems that drive clinical efficiency, reduce operational friction, and support data-driven decision-making for healthcare providers and industry stakeholders.
🦷 At Pearl AI, I contribute to the development and scaling of production-grade diagnostic models and inference platforms deployed across real-world dental practices. My work focuses on improving model reliability, streamlining integration, and delivering AI solutions that generate measurable clinical and operational value at scale.
📚 In parallel, I teach Deep Learning and Computer Vision, with a strong emphasis on applied methodologies, real-world deployment constraints, and the translation of research outcomes into production-ready solutions.
| Project | Description |
|---|---|
| 🚀 YOLO v11 Open Source | Clean, modular, Apache 2.0 licensed YOLOv11 implementation in pure PyTorch. Multi-task support: detection, segmentation, pose estimation. |
| 🩻 Chest X-Ray Detection App | End-to-end chest X-ray pathology detection application with deep learning. |
| 🦷 3D Mesh Segmentation | Teeth segmentation on 3D dental meshes — MICCAI 2022 Challenge data. |
| 🎯 Certainty Pooling for MIL | Novel pooling strategy for Multiple Instance Learning in medical imaging. |
| 🎨 Chest X-Ray Generative Models | Generative models (GANs, Diffusion) for synthetic chest X-ray generation. |
SISTR: Sinus and Inferior alveolar nerve Segmentation with Targeted Refinement on CBCT images
Laura Misrachi, Emma Covili, Hippolyte Mayard, Christian Alaka, Jérémy Rousseau, Willy Au
📄 medRxiv
Pre-Training with Diffusion models for Dental Radiography segmentation
Jérémy Rousseau, Christian Alaka, Emma Covili, Hippolyte Mayard, Laura Misrachi, Willy Au
📄 arXiv · Deep Generative Models @ MICCAI 2023
Burning Glass Technologies' data use in policy-relevant analysis (Contribution)
Emile Cammeraat, Mariagrazia Squicciarini
📄 OECD Science, Technology and Industry Working Papers, 2021
| Degree | Institution | Year |
|---|---|---|
| 🎓 M.Sc. Computer Vision & Medical Imaging (MVA) | ENS Paris-Saclay | 2021 |
| 🎓 M.Sc. Artificial Intelligence (IASD) | Dauphine PSL | 2020 |
| 🎓 B.Sc. Applied Mathematics | Dauphine PSL | 2018 |
- Deep Learning for Image Analysis — Dauphine-PSL, Master IASD
- Deep Learning — Dauphine-PSL Tunis
- Deep Learning for Image Analysis — Dauphine-PSL Tunis
- Introduction to Deep Learning — Sorbonne Data Analytics, DU Program
- Introduction to Deep Learning — Datagong.io, Professional Training