Théo Galy-Fajou is a doctor in Machine Learning specialized in Bayesian inference methods. He is particularly interested in approximate Bayesian inference methods like sampling, applications to Gaussian processes and online learning. Throughout his Ph.D., Théo developed numerous open source projects in Julia and dived deep into software development. He is currently working for PlantingSpace as a Julia software developer and Bayesian researcher.
You can find me on Github , Mastodon , ResearchGate and Twitter .
I finally defended my thesis on the 07th of July! I will upload the final version of the thesis soon.