Federico Tomasi
Senior Research Scientist at Spotify
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolFederico Tomasi is a Senior Research Scientist based in London with 10 years of experience applying probabilistic and generative machine learning to music personalisation at Spotify. He holds a PhD in Computer Science focused on temporal graphical models and has strong foundations in user modelling and reinforcement learning. At Spotify he progressed from Research Scientist to Senior Research Scientist, translating research into personalized music experiences. He contributes to high-profile open-source ML tooling, including optimizations and fixes to TensorFlow Probability, reflecting hands-on engineering in probabilistic computation. Federico combines rigorous academic training with product-minded research, uniquely bridging temporal probabilistic models and scalable production systems. Colleagues describe him as the kind of scientist who iterates on both theory and implementation to make personalization tangible.
10 years of coding experience
5 years of employment as a software developer
High School, Conc. in Science, High School, Conc. in Science at E. FermiDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Università degli Studi di Genova
Italian, English
Github Skills (9)
machine-learning10
probabilistic-programming10
tensorflow10
python9
statistics9
linear-algebra8
bayesian-methods7
deep-learning6
deeplearning-ai6
Programming languages (6)
Github contributions (5)
tensorflow/probability
Sep 2020 - Sep 2020
Probabilistic reasoning and statistical analysis in TensorFlow
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 1 commit, 5 PRs in 1 day
Contributions summary:Federico primarily focused on optimizing and refining the codebase within the TensorFlow Probability library. Their contributions include fixing indexing issues, optimizing the KL divergence computation for the `MatrixNormalLinearOperator` distribution, and addressing linting issues to improve code quality. Additionally, the user addressed comments on the pull requests, indicating an engagement in code reviews and iterative improvements.
statisticspythonprobabilistic-reasoningdata-sciencedeep-learning
fdtomasi/probability
Feb 2020 - Jan 2023
Probabilistic reasoning and statistical analysis in TensorFlow
Contributions:17 pushes, 7 branches in 2 years 11 months
pythonprobabilistic-reasoningdataminingstatisticalmachine-learning
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