Yasser Ebrahimian Ghajari | Remote Sensing | Best Researcher Award

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Dr. Yasser Ebrahimian Ghajari | Remote Sensing | Best Researcher Award

Assistant Professor, Babol Noshirvani University of Technology, Iran

Dr. Yasser Ebrahimian Ghajari is an Assistant Professor at Babol Noshirvani University of Technology, specializing in Geospatial Information Systems (GIS) with extensive academic, research, and professional contributions in geomatics and environmental applications. He holds a Ph.D. in GIS from Malek-Ashtar University of Technology, where he graduated as a top student, along with an M.Sc. in GIS from K. N. Toosi University of Technology and a B.Sc. in Surveying Engineering from Tabriz University. Dr. Ghajari has served as Head of the Geomatics Group at the Vice-Presidency for Science and Technology of Iran and is the Founder and Head of the GIS Scientific Association of Mazandaran Province. His professional achievements include leading numerous applied projects such as seismic microzonation, environmental auditing, sewage network geodatabases, infrastructure GIS development, and climate change monitoring using GPS observations. He has contributed significantly to the development of GIS-based environmental information management systems and spatial decision support systems, particularly in water resource and river basin management. With 11 publications, 106 citations, and an h-index of 5, Dr. Ghajari has established himself as a recognized researcher while also serving as a reviewer for multiple national and international journals in geomatics, environmental sciences, and remote sensing. In addition to research, he has taught a wide range of specialized courses including GIS, cadastre, spatial databases, decision support systems, photogrammetry, and advanced programming. His memberships include the National Elite Foundation of Iran and several scientific associations related to GIS, remote sensing, and surveying. His work reflects a blend of academic excellence, leadership, and practical application.

Profile:  Scopus  |  Google Scholar

Featured Publications

Ebrahimian Ghajari, Y., Alesheikh, A. A., Modiri, M., Hosnavi, R., & Abbasi, M. (2017). Spatial modelling of urban physical vulnerability to explosion hazards using GIS and fuzzy MCDA. Sustainability, 9(7), 1274.

Ebrahimian Ghajari, Y., Alesheikh, A. A., Modiri, M., Hosnavi, R., Abbasi, M., & Sharifi, A. (2018). Urban vulnerability under various blast loading scenarios: Analysis using GIS-based multi-criteria decision analysis techniques. Cities, 72, 102–114.

Ahmadlou, M., Ebrahimian Ghajari, Y., & Karimi, M. (2022). Enhanced classification and regression tree (CART) by genetic algorithm (GA) and grid search (GS) for flood susceptibility mapping and assessment. Geocarto International, 37(26), 13638–13657.

Ebrahimian Ghajari, Y., & Barari Siavoshkolaei, M. (2019). Runoff production potential zoning using fuzzy GIS-MCDA models (case study: Tajan river basin). Journal of Geomatics Science and Technology, 9(1), 1–14.

Amirsoleymani, Y., Abessi, O., & Ebrahimian Ghajari, Y. (2022). A spatial decision support system for municipal solid waste landfill sites (case study: The Mazandaran Province, Iran). Waste Management & Research, 40(7), 940–952.

Pouya Ghadesi | Earth Science | Best Researcher Award

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Mr. Pouya Ghadesi | Earth Science | Best Researcher Award

Mr. Pouya Ghadesi | University of Mohaghegh Ardabili | Iran

Mr. Pouya Ghadesi is a dedicated researcher in the field of mechatronics and artificial intelligence. He earned his Bachelor of Science in Mechanical Engineering and Master of Science in Mechatronics from the University of Mohaghegh Ardabili, Iran. His research interests include deep learning, neural networks, image processing, machine learning, and object detection. As an independent researcher, he has contributed to projects involving advanced frameworks such as MobileNetV3 and optimization algorithms, with applications in land-use classification. His work emphasizes innovation, model design, data validation, and publication of impactful research in high-quality scientific journals.

Professional Profile

Google Scholar

Academic and Professional Background

Mr. Pouya Ghadesi is a passionate researcher specializing in mechatronics and artificial intelligence with a strong academic foundation in mechanical engineering and mechatronics from the University of Mohaghegh Ardabili, Iran. His scholarly interests span deep learning, neural networks, image processing, machine learning, and object detection. As an independent researcher, he has actively contributed to the development of advanced frameworks and optimization methods, particularly focusing on applications in land-use classification. His efforts in model design, data analysis, experimental validation, and scholarly writing highlight his dedication to advancing scientific knowledge and producing impactful research within the global academic community.

Research Focus

Mr. Pouya Ghadesi is an emerging researcher whose work centers on the integration of mechatronics and artificial intelligence, with a particular emphasis on deep learning, machine learning, neural networks, and image processing. His research explores advanced approaches to machine vision and object detection, aiming to improve accuracy and efficiency in practical applications. He has contributed to the design and implementation of innovative frameworks that combine optimization methods with intelligent models, demonstrating his ability to address complex computational challenges. His focus reflects a commitment to advancing intelligent systems that can support real-world technological and scientific development.

Publication Top Notes

Improving accuracy of land-use classification through MobileNetV3 and Greedy Osprey Optimization

Year: 2025 | Cited by: 1

Conclusion

Mr. Pouya Ghadesi is a promising researcher with a strong background in mechanical engineering and mechatronics, focusing on artificial intelligence, machine learning, and image processing. His innovative work on the MobileNetV3 framework with the Greedy Osprey Optimization algorithm demonstrates both creativity and technical skill in land-use classification. Although at an early career stage, he shows great potential for impactful contributions, with opportunities to expand publications, international collaborations, and industrial applications, making him a strong candidate for the Best Researcher Award.