Building Intelligent and Trustworthy AI Systems
for Cybersecurity and Network Defense

I am a researcher in Artificial Intelligence and Cybersecurity, currently pursuing a Master of Engineering in Digital Security and Networks at Institut Supérieur d'Électronique de Paris (ISEP), France. My research focuses on developing intelligent, scalable, and explainable machine learning systems for intrusion detection, anomaly detection, and network security.

My work integrates machine learning, deep learning, explainable artificial intelligence (XAI), and network analytics to address emerging cybersecurity challenges in real-world environments. I am particularly interested in trustworthy AI, adaptive network defense, and intelligent security systems capable of operating effectively in dynamic and large-scale infrastructures.

I currently contribute to research on explainable anomaly detection in healthcare systems at LISITE, ISEP, where I investigate interpretable deep learning models for disease prediction and clinician-oriented AI explanations. My previous research explored the fusion of deep learning architectures in Intent-Driven Networks for real-time intrusion detection using the CIC-IDS2017 benchmark.