Dr. Lyes Saad Saoud is a Research Scientist specializing in artificial intelligence, robotics, and machine learning, with a rich academic background in physics, electronics, and renewable energy. He earned his D.Sc. and M.C.A. degrees (empowerment to direct research) in physics, with a specialization in renewable energies, from the University of Boumerdès, Algeria, in January 2015 and February 2017, respectively. His credentials have been officially recognized with U.S. degree equivalency.

From 2019, Dr. Saad Saoud served as an Associate Professor at the University of Boumerdès, where he also held academic leadership roles, including Head and Scientific Council Member of the Department of Electrical Systems Engineering and the Faculty of Technology. He also holds qualifications as an Engineer and Magister in Electronics, reflecting his interdisciplinary expertise.

Currently, his research focuses on integrating AI with autonomous systems for advanced applications in robotics, digital health, and environmental conservation. His expertise spans multi-modal AI, semantic SLAM, time-series forecasting, and real-time data processing, enabling the development of innovative solutions across diverse domains.

Recent projects include:

• HuBot – a pioneering bio-inspired robotic platform designed for non-disruptive studies of Houbara bustard behavior, merging multi-modal perception with semantic AI models for ecological research.

• AutoCoralMatch – an AI-powered pipeline for automated coral bleaching assessment, integrating dehazing, foundation models, and CoralWatch protocols to support scalable marine monitoring.

• Wearable AI Systems – advanced models for knee joint angle prediction and health monitoring using sensor fusion and deep learning architectures.

• Autonomous Underwater Robotics – AI-driven perception and adaptive mapping systems for exploration, aquaculture monitoring, and marine conservation.

• Renewable Energy Forecasting – machine learning algorithms for time-series prediction of supply and demand, improving renewable integration into modern power grids.

His broader research interests include environmental sustainability, digital health, vision-based navigation, hybrid systems, fuzzy logic, renewable energy, and cybersecurity.

Dr. Saad Saoud has contributed extensively to the international scientific community through conference participation, technical committee memberships, and invited talks. He also serves as a reviewer for leading journals, including:

• IEEE Transactions on Neural Networks and Learning Systems

• IEEE Access

• Transactions of the Institute of Measurement and Control (SAGE)

• Journal of Renewable and Sustainable Energy (AIP)

• Neurocomputing (Elsevier)

• Neural Processing Letters (Springer)

With a proven record of applied research, project leadership, and collaboration, Dr. Saad Saoud is committed to advancing AI-driven robotics and delivering impactful solutions at the intersection of technology, sustainability, and healthcare innovation.