Zag ElSayed

Zag ElSayed is an Assistant Professor at the University of Cincinnati's CECH School of Information Technology. He holds a PhD in Computer Engineering from the University of Louisiana at Lafayette (2016) with prior degrees from Alexandria University (2005-2010). His research focuses on Brain-Computer Interfaces (BCI), VLSI design, Cybersecurity, AI, and Green Computing. He has collaborated on grants totaling over $250K, including projects on IoT cybersecurity education and mobile app development for corrections systems.

Research interests include BCI systems for epilepsy prediction, low-power VLSI architectures for neural implants, and AI-driven solutions for healthcare IoT and cyber threats. Notable work includes a LiteLSTM architecture for RNN optimization, green computing metrics, and transfer learning for medical imaging (e.g., CT scan classification). He also explores cybersecurity challenges in smart homes and IoT devices, including intrusion detection and cryptojacking prevention.

Grants include a 2020-2022 cybersecurity education grant ($249K) and a 2021-2024 federal grant for correctional practices via mobile/web platforms. His lab affiliations include collaboration with Cincinnati Children's Hospital Neurology Research. Recent presentations address topics like BCI chronology and AI in smart city traffic systems.