Summary
Julien Diot is a data scientist and PhD candidate at The University of Tokyo with eight years of experience applying statistical modeling, image processing, and machine learning to agricultural and clinical problems. He specializes in optimizing plant breeding schemes and has a track record of building practical tools—from UAV-based crop detection and plant-counting algorithms to R-Shiny applications for Bayesian clinical trial design. Julien combines academic rigor with product-minded development, contributing to both university research and industry projects at ListenField and Sanofi. Fluent in Python, R and GIS tool development, he bridges ecology, agronomy and data science to deliver reproducible, domain-aware solutions. An often-overlooked strength is his experience translating research prototypes into teaching and decision-support apps, such as a serious game for selective breeding used in master-level education.
8 years of coding experience
1 year of employment as a software developer
Engineering degree (Master of science.) Data-Science for agronomy and food-industry, Data-Science, Agronomy, Engineering degree (Master of science.) Data-Science for agronomy and food-industry, Data-Science, Agronomy at Montpellier SupAgro
Doctor of Philosophy - PhD, Agriculture, General, Doctor of Philosophy - PhD, Agriculture, General at Univerity of Tokyo
CPGE (preparatory classes) BCPST, Biology, Chemistry, Physic, Math, Geology, Admis au concours A sur liste principale, CPGE (preparatory classes) BCPST, Biology, Chemistry, Physic, Math, Geology, Admis au concours A sur liste principale at Lycée Hoche, Versailles
Master's degree Data-Science, Applied Mathematics, Statistics, Master's degree Data-Science, Applied Mathematics, Statistics at Université Rennes 2
French, English, Japanese