Hamdy Soliman

Hamdy Soliman, PhD, is a Professor in the Department of Computer Science & Engineering at New Mexico Tech. His research focuses on computer networks security, neural networks, and wireless sensor networks. He has pioneered a novel encryption algorithm surpassing AES in speed and security against insider attacks, and holds five related security patents. His work in machine learning includes modeling with neural networks (e.g., LVQ, BP, BAM) for big-data management, image processing, and sensor network applications.

Research interests span secure mobile networks, cloud computing, and smart sensor systems for environmental monitoring (e.g., forest fire prediction). He has also explored healthcare applications via chatbots and AI-driven medical imaging (e.g., VGG16 for breast cancer detection). Recent work critiques the energy inefficiency of large language models and proposes optimized architectures.

Publications emphasize anomaly detection in wireless sensor networks, malware analysis in Android systems, and ensemble learning for social media content moderation. His contributions include routing protocols (e.g., SCWRRHA) and cloud data center failure prediction systems (Failuresim). No scientific awards explicitly listed, but his patent portfolio and prolific publishing reflect industry impact.

Advising and grants: While no advisees or grants are explicitly mentioned, his extensive publications suggest active mentoring of student researchers. His work on drone-based search-and-rescue systems (Project Vulture) indicates interdisciplinary collaboration in robotics and emergency response.