I am a young engineer & a Ph.D. student, and you are welcome to my web-portfolio.
I currently work as a Ph.D. student at the Orange company, in collaboration with INRIA labs (LACODAM). In the context of servers & infrastructure performances, I manipulate Time Series to do predictions. I code Machine Learning algorithms and user interfaces to improve the Capacity Planning at Orange.
I talk Scala, I am a DevOps, I love CI, FP, Ansible/Jenkins/Docker, I build tested & stable software.
You will find on this website some information about me, my skills, and about some of my projects.
Paris - France
Guitarist / Singer / Music player & producer
Regular runner (goal: semi-marathon in 6 months), occasional swimmer, love long hikes and nature activities
2017 - 2020: Ph.D. student at Rennes 1 University
mid-2016 - 2017: ERASMUS in Roskilde University, Denmark
2014 - 2017: student at the engineering school ENSSAT Lannion - Computing Science
2012 - 2014: D.U.T GEII Rennes (Technical Degree in Electronics & Computing Sciences)
Fondamentaux pour le Big Data
2017: China, Italy, Croatia, Slovenia, etc.
2016: Japan (15 days), Lisboa (7 days), Ireland (10 days), Denmark (5 months)
2015: Scotland, Glasgow (30 days)
2014: Ireland (3 months), Athlone AIT during an internship
& many others. . .
English: fluent & good technical skills (B2 level)
Spanish: basic knowledge
Danish: basic knowledge
Functional programming: Scala, 3 years experience, daily use. Followed the Scala specialisation on Coursera.
Git: Daily use, advanced workflow (branch, checkout, tags, ...).
Object-oriented programming: Java, 4 years experience, several projects.
C: robust experience (loop invariant, strict methodology & concepts, graphs).
Databases: SQL (MySQL, PostgreSQL...) / NoSQL (MongoDB) / Time Series databases (influxDB)
Click on a project to learn more!
Clone of Boulder Dash, done in Java, use of MVC pattern.
Use of R to analyse a Dataset concerning the sinking of the Titanic. Machine Learning models used to predict the survivors of the crash.
Use of Scala to scrap a webpage containing data about beers. The goal is to learn how to scrap the web to create my own datasets.