I am a researcher in Artificial Intelligence and Cybersecurity and a Master of Engineering candidate in Digital Security and Networks at Institut Supérieur d'Électronique de Paris (ISEP), France. My current research is conducted within the LISITE Research Laboratory under the supervision of Dr. Yousra Chabchoub. My research interests span Artificial Intelligence, Cybersecurity, Explainable AI (XAI), anomaly detection, intelligent network systems, and trustworthy machine learning for real-world applications.

My work integrates machine learning, deep learning, explainable artificial intelligence, and network analytics to address emerging challenges in cybersecurity and healthcare. I am particularly interested in developing transparent, reliable, and scalable AI systems capable of supporting decision-making in complex and dynamic environments. My research seeks to bridge advanced AI methodologies with practical challenges in network security, anomaly detection, and intelligent digital infrastructures.

At LISITE, I investigate explainable anomaly detection in healthcare systems, leading to the development of the paper "A Multi-tier Explainable AI Architecture for the Prediction of Cardiovascular Diseases", accepted for presentation at the International Conference on Information and Computer Technologies (ICICT 2026). Prior to this, I conducted research at African University of Science and Technology (AUST), Abuja, under the supervision of Dr. Rajesh Prasad, Dean and Associate Professor of the School of Computing and Information Technology. This work explored the fusion of deep learning architectures in Intent-Driven Networks for real-time intrusion detection using the CIC-IDS2017 benchmark and resulted in the book chapter "Fusion of Deep Architectures in Intent-Driven Networks for Intrusion Detection".