Massimo Quadrana
Summary
👤
SeniorMassimo Quadrana is a machine learning researcher with 11 years of experience specializing in recommender systems and sequential prediction, currently applying his expertise at Apple. He holds a PhD in Computer Engineering from Politecnico di Milano where his research on session- and sequence-based recommenders influenced music, e-commerce, and cross-domain recommendation approaches. His industry work includes leading recommendation and NLU efforts at Pandora—building mood-aware personalized feeds and voice-query engines handling tens of thousands of requests—and developing scalable personalization algorithms and Bayesian hyperparameter tuning at ContentWise. Comfortable bridging research and production, he has published work on RNN-based session recommenders and has hands-on experience with large-scale data tooling and deep learning frameworks. Based in Stony Stratford, UK, Massimo combines rigorous academic grounding with a track record of shipping scalable ML systems in music and media domains, often tackling noisy, real-world datasets.
11 years of coding experience
Github Skills (17)
recurrent-neural-networks10
sequence10
sequence-modeling9
jupyter-notebook9
recommender9
machine-learning7
recommender-system7
python1
datasets1
data-science1
pandas1
filtering1
keras1
implicit1
collaborative-filtering1
Programming languages (2)
Github contributions (5)
mquad/recsys-course-2016-pub
Oct 2016 - Mar 2017
Course on Recommender Systems 2016 - Politecnico di Milano
Contributions:34 commits, 26 pushes, 1 branch in 5 months
recommender-system
mquad/hgru4rec
Jun 2017 - Jan 2020
Code for our ACM RecSys 2017 paper "Personalizing Session-based Recommendation with Hierarchical Recurrent Neural Networks"
Contributions:6 commits, 2 PRs, 7 pushes in 2 years 7 months
recurrent-neural-networks
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.