About me

Hey there! My name is Thomas Simonini and Iโ€™m 25 years old. I work as a Reinforcement Learning Research Scientist at Dataiku in Paris and Iโ€™m passionate about Reinforcement Learning research and education.

After a Bachelor Degree of Law and Political Sciences in 2016, I decided to self study during 2 years mathematics, deep learning and deep reinforcement learning. I'm graduated from Deep Learning Foundations and Artificial Intelligence Nanodegree by Udacity.

I combined my two passions by founding Deep Reinforcement Learning Course, a free open source series of articles and videos from beginner to expert where we learn the main algorithms and how to implement them with Tensorflow and PyTorch. The course is a success with + 35,000 claps and about 5,000 readers per week.

I believe that innovation comes from sharing knowledge with open education thatโ€™s why my course is free and why my projects are open sourced.

I have 2 missions:

  • The first is having an impact in Reinforcement by building free educational content and working on research projects.
  • The second is to create video games that spark impactful experiences and emotions to the players.

My resume

My recent projects

Shoot Moo

ShootMoo (Minecraft Mod)

[WORK IN PROGRESS] A minecraft mod where the goal is to shoot your opponents with cows. ๐Ÿฎ


Game Dev Youtube Channel

[WORK IN PROGRESS] This Youtube Channel will focus on people who are part time indie game devs. And share with them my productivity tips, my adventures, my advices and some tutorials.

Deep Reinforcement Learning Course

Deep Reinforcement Learning Course ๐Ÿ•น๏ธ

A free course about Deep Reinforcement Learning, where we'll learn the main algorithms, and how to implement them with Tensorflow and PyTorch.

Start Learning

CatDCGAN ๐Ÿฑโ€๐Ÿ’ป

An open source AI that generates pictures of cats ๐Ÿฑโ€๐Ÿ’ป.

Look at the cats ๐Ÿ˜ธ

My recent talks

Rework 19

RE-WORK Deep Learning Summit 2019: Curiosity Driven Learning

Curiosity Driven Learning is one of the most exciting and promising strategy in deep reinforcement learning: we create agents that are able to produce rewards and learn from them. In this workshop, youโ€™ll learn what is curiosity, how it works, and understand the process of how an agent generates this intrinsic reward using a trained agent in a video game environment. By the end of this workshop, you'll be able to understand how curiosity driven learning agents work and the main elements needed to implement them.

Learn More
Rework simonini thomas

RE-WORK Deep Learning Summit 2019: Interview

Watch The Interview