Vittorio Mazzia
Senior Research Scientist Alexa AI at Amazon
Turin, Piedmont, Italy
Summary
👤
Senior🎓
Top SchoolVittorio Mazzia is a Senior Research Scientist at Amazon (Alexa AI / AGI) with eight years of experience bridging deep learning research and production-scale conversational systems. He holds a PhD from Politecnico di Torino where he developed algorithms for perception, autonomous navigation and efficient embedded AI, and he now focuses on the capacities and limits of large neural models with an emphasis on neural efficiency and generalization. At Amazon he has driven multilingual context providers, temporal reasoning strategies for conversational agents, and lightweight knowledge-editing methods that cut retraining time and data needs. Vittorio combines academic rigor with hands-on engineering—contributing full‑stack tooling for large vision datasets (e.g., Open Images v4) and optimizing models for latency and multilingual deployment. Based in Turin, he also brings an unusual creative background in music composition, which informs his interest in prosody and multimodal reward models for speech LLMs.
8 years of coding experience
8 years of employment as a software developer
Music Theory and Composition, Music Theory and Composition at I.S.S.M. Conservatorio Guido Cantelli di NovaraDoctor of Philosophy - PhD, Artificial Intelligence, cum laude, Doctor of Philosophy - PhD, Artificial Intelligence, cum laude at Politecnico di Torino
English, French, Italian
Stackoverflow
1reputation
106reached
0answers
1question
Github Skills (9)
computer-vision10
opencv10
python10
image-processing9
multithreading9
android6
wifi6
transmission6
java6
Programming languages (6)
Github contributions (5)
EscVM/OIDv4_ToolKit
Jul 2018 - May 2019
Download and visualize single or multiple classes from the huge Open Images v4 dataset
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:34 commits, 3 PRs, 28 pushes in 9 months
Contributions summary:Vittorio primarily contributed to the Open Images v4 toolkit by implementing features for downloading and visualizing images from the dataset. They introduced multithreading to improve download performance and enhanced the visualizer, fixing menu navigation and adding labels. The changes also involved updating the bounding box format for label files, ensuring the software correctly uses the expected format.
visualizeopen-imagespythondataset
EscVM/EscVM_YT
Jul 2020 - Jan 2023
EscVM YouTube Channel Repository. Start from Notebooks ⬅️
Contributions:61 commits, 1 PR, 67 pushes in 2 years 6 months
artificial-intelligencedeep-learningmachine-learningyoutube
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