Filippo Bianchi
Professor at NORCE Norwegian Research Centre
Tromsø, Troms og Finnmark, Norway
Summary
👤
Senior🎓
Top SchoolFilippo Bianchi is a Professor of Machine Learning at UiT the Arctic University of Norway with eight years of research and industry experience at the intersection of machine learning, dynamical systems, and complex networks. He applies his research to energy analytics and remote sensing, blending theoretical insight with domain-focused applications through roles at UiT and NORCE. Filippo has a strong academic pedigree (PhD in AI from Sapienza) and international experience including visiting positions in Italy, Switzerland, and Canada. He contributes to open-source graph ML tooling—adding real-world datasets and dataset management improvements to the popular Spektral library—demonstrating practical impact on graph neural network research workflows. Known for bridging rigorous mathematics with applied sensing and energy problems, he combines long-term academic leadership with hands-on engineering contributions.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Artificial Intelligence, Doctor of Philosophy (Ph.D.), Artificial Intelligence at Sapienza Università di RomaHigh school diploma, Scientific, High school diploma, Scientific at Liceo A. Righi
English, Italian
Github Skills (20)
preprocessing10
python10
load-data10
preprocess10
data-set10
data-management10
numpy10
datasets10
data-preprocessing10
keras10
data-loading10
deeplearning-ai10
dataprep10
deep-learning10
tensorflow10
Programming languages (3)
Github contributions (5)
danielegrattarola/spektral
Jul 2022 - Jul 2022
Graph Neural Networks with Keras and Tensorflow 2.
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 1 PR, 2 comments in 1 day
Contributions summary:Filippo contributed to the project by adding and modifying dataset implementations for graph neural networks. They added the Flickr and DBLP datasets, incorporating data loading, pre-processing, and graph construction logic. The changes also included updates to existing citation datasets and overall dataset management within the project, improving the library's functionality for graph-based machine learning tasks. The contributions demonstrate a focus on expanding the project's dataset support.
pythondeep-learninggraph-deep-learningneural-graphneural-networks
FilippoMB/Diffusion_models_tutorial
Aug 2022 - Nov 2022
Contributions:24 commits, 21 pushes, 2 comments in 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.