Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Mr. Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Ecole Polytechnique de Tunisie | Tunisia

Oussama El Othmani is an emerging researcher and software engineer whose work bridges artificial intelligence, explainable machine learning, and applied computer engineering. He is currently pursuing a PhD in ETIC, following a strong academic foundation in computer engineering and preparatory mathematics–physics, with rigorous training in artificial intelligence, advanced learning algorithms, computer architecture, databases, and software methodology. Professionally, he has contributed to complex, mission-critical software systems, working across the full software development lifecycle while applying agile methodologies, object-oriented design, and hardware-aware optimization. His research interests focus on explainable and interpretable AI, machine learning, rough set theory, soft computing, computer vision, natural language processing, and AI applications in healthcare and high-stakes decision systems. He has led and contributed to multiple applied AI projects, including medical chatbots, diagnostic decision-support systems, blood anomaly detection, and antibiotic resistance classification. His scholarly output includes peer-reviewed publications in applied AI, He has also gained recognition through research-driven projects aligned with national and institutional initiatives. Overall, his profile reflects a strong balance of academic research, applied innovation, and real-world impact, positioning him as a promising contributor to the future of trustworthy and explainable artificial intelligence.

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Amir Hossein akbari | Engineering and Technology | Research Excellence Award

Dr. Amir Hossein akbari | Engineering and Technology | Research Excellence Award

Iran University of Science and Technology | Iran

Amir Hosein Akbari is an accomplished researcher in industrial engineering with a strong record of scholarly impact his academic background is grounded in advanced industrial engineering education, complemented by progressive research experience spanning optimization, decision sciences, and intelligent systems. His professional experience includes active involvement in high-quality research collaborations and contributions to applied and theoretical studies addressing complex industrial and societal problems. His core research interests focus on supply chain management, optimization, meta-heuristic and evolutionary algorithms, scheduling, decision support systems, and artificial intelligence–driven industrial applications, with several influential works in expert systems, soft computing, and manufacturing systems. His publications have appeared in high-impact venues such as Expert Systems with Applications, Soft Computing, and Neural Computing and Applications, reflecting both methodological rigor and practical relevance. Recognition of his work is demonstrated through strong citation performance and collaborations with well-established scholars in operations research and industrial engineering. Overall, his research portfolio highlights a consistent commitment to advancing intelligent optimization methods and decision-making frameworks, contributing valuable insights to academia and industry while strengthening the scientific foundations of modern industrial engineering.

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