Emanuele Frandi
Applied Scientist, JP Retail Science at Amazon
Tokyo, Japan
Summary
👤
Senior🎓
Top SchoolEmanuele Frandi is an applied scientist with a decade of experience building and prototyping machine learning solutions at the intersection of research and product, currently driving R&D for JP Retail Science at Amazon in Tokyo. Trained as a computational mathematician (PhD) with summa cum laude degrees in applied mathematics, he has deep expertise in large-scale optimization, SVMs, multilevel and derivative-free methods from his academic work and postdocs. In industry he has translated that theory into production-facing ML and data-science projects across roles at Cogent Labs and Amazon, leading models that address concrete business problems in consumer and retail. His background in recurrent neural models for neuroscience research at RIKEN and high-performance optimization gives him a distinctive edge in combining principled algorithms with scalable implementations. Colleagues describe him as someone who bridges rigorous research and pragmatic engineering to deliver novel, deployable ML technologies.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (PhD), Computational Mathematics, Doctor of Philosophy (PhD), Computational Mathematics at Università degli Studi dell'InsubriaMaster's Degree, Applied Mathematics, 110/110 summa cum laude, Master's Degree, Applied Mathematics, 110/110 summa cum laude at Università degli Studi di FirenzeLiceo Scientifico "A.M.E. Agnoletti"
English, French, Japanese, Italian
Github Skills (7)
keyboard7
macos4
karabiner3
hana1
react-native1
react1
macos-sierra1
Programming languages (1)
Github contributions (5)
efrandi/FW-SVMs
Oct 2015 - May 2016
Contributions:3 commits, 2 pushes, 1 branch in 6 months
efrandi/FW-Lasso
Oct 2015 - Oct 2015
Contributions:6 commits, 5 pushes, 1 branch in 4 days
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