Luca Invernizzi
Senior Staff Research Scientist Manager at Google
Zurich, Zurich, Switzerland
Summary
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Senior🎓
Top SchoolLuca Invernizzi is a Senior Staff Research Scientist Manager at Google with over a decade of experience specializing in information security and malware detection. He builds large-scale, data-driven systems that surface malicious and abusive behavior, and has led research into robust detection methods that reduce cybercriminal impact across products. His background spans academia (PhD in Computer Science from UC Santa Barbara), industry research, and hands-on security engineering—from designing ISP-scale traffic analysis systems to leading HIPAA-focused security consulting. Luca contributes to open-source and ML tooling (including backend and MLOps work on the popular keras-tuner project) and brings practical production experience in model tuning, artifacts uploading, and refactoring at scale. An avid competitor in hacking contests and former GNOME contributor, he blends offensive security intuition with a measured research mindset. He’s also pursued interdisciplinary interests from underwater robotics to executive business training, reflecting a curiosity that fuels pragmatic, cross-domain solutions.
10 years of coding experience
16 years of employment as a software developer
Executive MBA, Executive MBA at Quantic School of Business and TechnologyStudent, Engineering, Student, Engineering at Scuola Superiore 'Sant' Anna' di Studi Universitari e di PerfezionamentoMaster, Automation Engineering, Master, Automation Engineering at Università di PisaMathematics, Engineering, Mathematics, Engineering at University of Hawaii at ManoaDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at UC Santa Barbara
English, Italian, French, Spanish, German
Github Skills (7)
hyperparameter-optimization10
keras10
tensorflow10
python10
back-end-development9
machine-learning9
firebase8
Programming languages (2)
Github contributions (5)
keras-team/keras-tuner
May 2018 - May 2019
A Hyperparameter Tuning Library for Keras
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:36 commits in 1 year
Contributions summary:Luca focused on refactoring the result format within the Keras Tuner engine, specifically impacting the `HyperTuner` and `Instance` classes. This included modifications to how metrics and results are recorded, with adjustments to the saving of models and configurations. The user also implemented the upload of model configurations, weights and results to Firebase.
hyperparameterdeep-learningmachine-learningautomltensorflow
invernizzi-at-google/vagrant
Nov 2015 - Nov 2015
Contributions:1 push in 1 day
ansiblevagrantdockerenvironments
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