Dr. Marran Al Qwaid | Artificial Intelligence | Best Researcher Award

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Dr. Marran Al Qwaid | Artificial Intelligence | Best Researcher Award

Assistant Professor | Shaqra University | Saudi Arabia

Dr. Marran Al Qwaid is a distinguished academic and Vice Dean of E-Learning and Digital Transformation at Shaqra University, holding a Ph.D. in Computing and Information Systems. His extensive experience as an Assistant Professor in Computer Science reflects a strong foundation in Artificial Intelligence, cybersecurity, and digital innovation. Dr. Marran Al Qwaid has contributed significantly to research in Artificial Intelligence-driven optimization, secure data systems, and computational efficiency. His academic journey spans global institutions, earning degrees from reputed universities and professional certifications in Artificial Intelligence, cybersecurity, and leadership from renowned platforms. With publications in high-impact journals and participation in international conferences, he has established a profound presence in the field of Artificial Intelligence. His research explores Artificial Intelligence applications in secure computing, data privacy, and cyber defense, demonstrating advanced analytical and problem-solving skills. As an editor and committee member in multiple international journals and conferences, he showcases leadership in Artificial Intelligence research and digital transformation. Dr. Marran Al Qwaid has received recognition for his scholarly and administrative excellence, including appointments to key university committees related to Artificial Intelligence, cloud computing, and innovation governance. His technical expertise, combined with a vision for enhancing Artificial Intelligence education and application, marks him as a pivotal contributor to the digital future. His remarkable career underlines excellence in Artificial Intelligence teaching, research, and leadership. Scopus profile of 2 Citations, 4 Documents, 1 h-index.

Profile: Scopus

Featured Publication

1. Performance Optimization of Grounding System for Multi-Voltage Electrical Installation. (2025). Applied Sciences, Switzerland.

Yuyao Wang | Artificial Intelligence | Best Scholar Award

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Mr. Yuyao Wang | Artificial Intelligence | Best Scholar Award

Master's Candidate | Henan Polytechnic University | China

Mr. Yuyao Wang, a Master’s candidate in Cartography and Geographic Information Systems at Henan Polytechnic University, has made significant contributions to remote sensing and artificial intelligence integration for agricultural and environmental monitoring. His research primarily focuses on remote sensing image processing, land use classification, and artificial intelligence-driven multi-source data fusion. With strong expertise in applying artificial intelligence to satellite data interpretation, Mr. Wang has developed novel frameworks for rice field identification in mountainous regions and cloud removal techniques using SAR and optical imagery fusion. His innovative use of artificial intelligence in remote sensing enhances precision agriculture and sustainable land management practices. Mr. Wang’s professional journey reflects his commitment to applying artificial intelligence and geospatial analytics to complex real-world challenges. His works published in prestigious journals like Remote Sensing and PLOS ONE demonstrate robust analytical skills, methodological innovation, and interdisciplinary thinking powered by artificial intelligence. He continues to explore advanced artificial intelligence techniques for improving data accuracy and environmental insights, bridging gaps between technology and agricultural sciences. Mr. Wang’s achievements highlight excellence in artificial intelligence research, demonstrating potential for transformative advancements in geoinformatics and environmental sustainability. His dedication, scientific curiosity, and mastery of artificial intelligence tools reinforce his reputation as a promising researcher in remote sensing and GIS. 12 Citations, 3 Documents, 2 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Wang, Y., Cheng, J., Yuan, Z., & Zang, W. (2025). Research on rice field identification methods in mountainous regions. Remote Sensing, 17(19), 3356.

2. Wang, Y. (2025, March 19). A novel cloud removal method by fusing features from SAR and neighboring optical remote sensing images.