​Dr. Mahmoud Nazzal is an experienced researcher and educator specializing in machine learning security, robustness, and signal processing for communications. He is pursuing his PhD in Computer Engineering at the New Jersey Institute of Technology, USA. His research focuses on security in machine learning, including Graph Neural Networks (GNNs) and Generative Pretrained Transformer (GPT) language models, with applications in malicious domain detection and network traffic prediction.

Dr Nazzal has held multiple academic and research roles, including positions as a Research Assistant at NJIT, a Postdoctoral Research Fellow at Istanbul Medipol University, and a Lecturer at institutions such as Eastern Mediterranean University and the Izmir University of Economics. His teaching portfolio spans computer architecture, programming, robotics, and digital electronics courses.

With a robust signal processing and machine learning background, Dr. Nazzal has published extensively in leading journals and conferences. His work includes contributions to spectrum sensing, channel estimation, and adversarial machine learning. He has also been recognized with multiple awards, such as the Ross Fellowship and Best Paper at international conferences.

Dr. Nazzal's expertise extends to practical applications, including patent contributions in spectrum sensing and attack detection and professional affiliations with IEEE and ACM. His commitment to advancing security and machine learning positions him as a leader in his field.