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Aurelio Salvati

@aureliosalvati

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I build secure AI, federated learning, and IoT systems through research and hands-on engineering.

Italy

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What I'm looking for

I'm looking for opportunities to apply cybersecurity, AI, and distributed-systems work to practical products and research, while growing through hands-on engineering, international collaboration, and challenging security-focused projects.

I've advanced federated learning research at CNRS in Lyon, designing distributed training experiments and evaluating model performance across simulated nodes. My work contributed to a paper submitted to the Middleware conference.

I'm completing a Computer Engineering master's degree in Cybersecurity at the University of Naples Federico II, graduating with distinction, 110/110 cum laude. My academic work spans network security, cryptography, secure software design, and cyber threat analysis.

I build practical security and AI projects, including a Python multi-agent framework for automated repository security auditing using RAG and Gemini embeddings. I've also developed a controlled fake-access-point and MITM lab, a NIST-aligned secure web application, and a CNN-based image super-resolution system.

My international path includes studies in Italy, France, and China, with experience in parallel programming, distributed systems, embedded IoT, and secure software engineering. I ranked first in Leonardo's Ethical Hacking track and placed in the Top 10 in BIP's AI sentiment-analysis challenge.

Experience

Work history, roles, and key accomplishments

Research Intern

CNRS

Nov 2025 - Jun 2026 (7 months)

Advanced federated learning research for distributed AI systems, designing and running distributed training experiments and evaluating model performance across simulated nodes. Co-authored a paper submitted for review at the Middleware conference.

Federated Learning Distributed Systems PyTorch TensorFlow Experimental Design Research

Education

Degrees, certifications, and relevant coursework

University of Naples Federico II

Master's Degree, Computer Engineering

2023 -

Grade: 110/110 cum laude

Master's degree in Computer Engineering with a Cybersecurity specialization, graduating with distinction (110/110 cum laude).

Leonardo

Cybersecurity Deep Dive – Winter Course, Cybersecurity

2026 - 2026

Activities and societies: Ranked 1st in Ethical Hacking track; completed modules in Ethical Hacking, Cloud Security (Azure), and Cyber & Digital Innovation.

Completed the Cybersecurity Deep Dive Winter Course, ranking 1st in the Ethical Hacking track.