Simon Thomine

2024 -

Senior computer vision research engineer at Vitadx. I develop AI for pathology to assist medical professionals in early cancer detection. Our primary focus is bladder cancer, the 7th most common cancer in men, along with research into blood and thyroid cancers. By leveraging advanced computer vision and multimodal AI, we aim to enhance diagnostic accuracy and improve patient outcomes.

2021 - 2024

PhD in deep learning from UTT and Aquilae, specializing in unsupervised learning for anomaly detection in industrial applications. Led multiple research and development projects at Aquilae, focusing on industry and security solutions.

2019 - 2020

Semester abroad at Laval University in Quebec, Canada, focusing on master-level courses in deep learning and applied mathematics.

2017 - 2020

Engineering degree in computer vision application development from Telecom Saint-Etienne.

2015 - 2017

Preparatory classes for engineering schools at ENCPB, Paris.

Projects

Deep Learning Course in French aims to teach deep learning from scratch, requiring only basic Python and math knowledge. It offers a comprehensive introduction to core deep learning principles within a single GitHub repository with various notebook lessons. Making AI accessible to a wider audience is crucial in today’s world, given AI's growing presence in our daily lives.

3rd Place Cytologia Data Challenge. I participated in the Cytologia Data Challenge to contribute to advancing hematological diagnostics through AI. My goal was to detect and classify white blood cells in images from blood smears, and I am proud to have secured a third-place finish. ,winning a prize of 5000€.

Industrial Defect Generator a new library dessigned to generate synthetic industrial defects based on proposed methods from the litterature.

Distillation Industrial Anomaly Detection regroups advanced methods utilizing knowledge distillation for industrial unsupervised anomaly detection.