Introduction

I’m a tech-driven problem solver with a traditional heart — raised on curiosity, discipline, and a love for creating things that make life better. From AI-based robotic teleoperation to automotive cybersecurity, I’ve worked across Europe on projects that merge machine intelligence with real-world safety. I believe in secure innovation — technology that’s powerful, ethical, and human-centered.

Recent Work: Master Thesis

My current research focuses on developing an AI-driven automated threat detection and incident-response framework that can detect and react to cybersecurity threats in real time. The system integrates machine learning algorithms with cybersecurity automation pipelines to improve detection speed, precision, and adaptability. It applies boosting, anomaly detection, and ensemble models to analyze behavioral patterns in large-scale datasets. The framework also features a rule-based SOC module that autonomously correlates alerts, prioritizes threats, and executes mitigation steps, minimizing manual effort and response time. It bridges the gap between human-driven analysis and intelligent automation, creating a scalable and self-learning security system that enhances cyber resilience.

My Accomplished Projects

I believe real learning happens when ideas turn into working prototypes. From Germany to Italy, France, and Spain, my projects reflect a journey through cybersecurity, robotics, AI, and IoT — built with passion, collaboration, and a lot of late-night caffeine.

JetBot Teleoperation (NVIDIA Jetson Nano)

AI & Robotics: JetBot Teleoperation

I, along with my team, developed an AI-powered JetBot using NVIDIA Jetson Nano, capable of responding to gamepad, keyboard, and voice commands.
The project combined real-time object detection, environmental Q&A, and manual teleoperation, showcasing how robotics and machine learning can work together seamlessly. It also deepened my understanding of edge AI deployment and parallel processing.

Automotive Cybersecurity Academy 2024 – Italy

As part of the ACSA 2024 program at the University of Salerno, I collaborated with international peers on a project about predictive maintenance alerts in connected vehicles.
We analyzed sensor telemetry and anomaly patterns to predict early signs of component failure, integrating cybersecurity assessments based on TARA (Threat Analysis and Risk Assessment).
The project enhanced both my technical and teamwork skills while giving me insight into real-world automotive cyber defense.

Smart Supermarket Digital Price Tag System

I, along with my team, designed a complete IoT-based retail automation system using ESP8266 microcontrollers, Node-RED, InfluxDB, and Grafana.
The system enables wireless, real-time updates of product prices across shelves and provides live visual analytics through dashboards.
This project strengthened my knowledge of data pipelines, edge devices, and MQTT-based communication.

Autonomous Soil Quality Detection System

In this project, along with my team, I built an IoT sensor device that monitors soil pH, moisture, and nutrient levels to guide precision agriculture decisions.
It uses multi-sensor integration and wireless data transmission to send readings to a remote dashboard for real-time analysis.
This experience connected my IoT skills with sustainability and green tech applications.

Microgrid Optimization & Autonomous Solar Tracker (THM–CESI France)

Collaborating with researchers from CESI, France, I, as a "Team Leader", led & contributed to a simulation model for microgrid performance optimization.
I developed Python-based PV and battery simulation scripts using PVGIS data and designed an autonomous solar tracker to improve energy efficiency.
This project gave me practical exposure to energy systems, optimization algorithms, and cross-border teamwork.