Portrait image of Florian Ravasi

Data scientist/engineer with an emphasis on Deep Learning and Reinforcement Learning looking forward to developing adapted artificial intelligence for industry. My spectrum of skills can roughly be summarized as follows:

- Conducted research projects: Hydropower optimization, circuit architecture generation and epidemics mitigation using Reinforcement Learning
- Software engineering experience: Agile Scrum to design an Android app, library for Onion Routing (i.e. Tor browser to enter deepweb)
- Solid mathematical background in the foundations of data science: Learning Theory, Statistics, Signal Processing and Information Theory
- Machine Learning: Classification, Unsupervised, Semi-Supervised, Few-shots Learning , Regression, (Geometric) Deep Learning, Reinforcement Learning
- Data engineering: (Py)Spark, Hive, Ray (including deploying large scale reinforcement learning), SQL, Pandas etc.
- Optimisation (theoretical and hands on experience with hydropower): Mixed Integer Linear Programming, Successive Linear Programming, Dynamic Programming etc.
- Programming languages: Python (proficient with known librairies such as Numpy, PyTorch etc.), Scala, Java, Go and C.

AMLD EPFL 2022 / Speakers

Michael Bronstein

Oxford / Twitter / IDSIA

Max Welling

Distinguished Scientist, Microsoft Research

Samy Bengio

Senior Director, AI and Machine Learning Research, Apple

Regina Barzilay

Professor of Electrical Engineering and Computer Science, MIT

Melanie Mitchell

Davis Professor, Santa Fe Institute

Thomas Wolf

Co-founder and Chief Science Officer, Hugging Face

AMLD / Global partners