Gustavo Bertoli
Research Scientist at Airbus
Germany
Summary
👤
Senior🎓
Top SchoolGustavo Bertoli is a research scientist and cybersecurity architect with 10+ years of experience designing secure embedded and distributed systems for aerospace platforms. He has advanced product security and research from concept to TRL3–4 at Airbus and Airbus Defence & Space, and led security-by-design efforts and vulnerability monitoring for Embraer’s commercial and defense products. His background spans avionics software, electrical systems, and onboard maintenance algorithms—work that delivered >$1M in savings and new data-service revenue. Gustavo pairs a PhD-level academic foundation from ITA with hands-on implementation of certification-driven standards (DO-178/254 and others) in safety-critical contexts. He also contributes to federated learning tooling, improving examples and adding a FedAvgM baseline to the popular Flower framework, reflecting interest in applied ML for distributed systems. Based in Germany, he combines deep aerospace domain expertise with practical cybersecurity and embedded-systems engineering.
10 years of coding experience
14 years of employment as a software developer
BS Electrical Engineering, BS Electrical Engineering at Universidade Estadual Paulista Júlio de Mesquita FilhoDoctor of Philosophy (Ph.D.) Electronics and Computer Engineering, Doctor of Philosophy (Ph.D.) Electronics and Computer Engineering at Instituto Tecnológico de Aeronáutica - ITA
Portuguese, English, Spanish, German
Stackoverflow
48reputation
28kreached
7answers
3questions
Github Skills (18)
python10
scikit10
machine-learning10
tensorflow10
federated-learning10
scikit-learn10
deeplearning-ai9
deep-learning9
web-framework8
app-framework8
pytorch8
application-framework8
clang6
classification6
bpf6
Programming languages (10)
Github contributions (5)
adap/flower
Mar 2022 - Jul 2022
Flower: A Friendly Federated AI Framework
Role in this project:
ML Engineer
ML EngineerContributions:15 reviews, 2 commits, 12 PRs in 4 months
Contributions summary:Gustavo primarily contributed to examples and documentation within the Flower framework. Their work included correcting references and parameters in a simulation example (sim.ipynb), fixing an example in the sklearn-logreg-mnist directory, and adding a baseline implementation for FedAvgM, a federated learning algorithm. Additionally, the user collaborated on examples for custom metrics, demonstrating an understanding of the framework's application.
federated-analyticsfederated-learning-frameworkmachine-learningkeras-federated-learningflower
gubertoli/ProbingDataset
Oct 2019 - Jul 2022
Contributions:1 release, 103 commits, 7 PRs in 2 years 9 months
nmapscansecuritynsedataset
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