Yasser Ebrahimian Ghajari | Geo-Informatics | Best Researcher Award

Assist. Prof. Dr. Yasser Ebrahimian Ghajari | Geo-Informatics | Best Researcher Award 

Assistant Professor | Babol Noshirvani University of Technology | Iran

Dr. Yasser Ebrahimian Ghajari is a distinguished scholar, educator, and leader in the field of geomatics, with expertise spanning surveying engineering, GIS, remote sensing, spatial data analysis, and knowledge-based technology development. He holds a Ph.D. in Surveying Engineering (GIS Track), an M.Sc. in Civil Engineering specializing in Surveying and GIS, and a B.Sc. in Surveying Engineering, all achieved with top academic rankings. Professionally, he serves as a faculty member at Babol Noshirvani University of Technology and has held prominent leadership roles as founder and director of national-level geomatics initiatives, head of scientific associations, and board member in engineering and mining organizations. His research interests include geospatial data modeling, GNSS systems, AI-driven spatial applications, disaster and crisis management, urban and environmental analysis, land and property management, and smart infrastructure monitoring. He has supervised and executed numerous large-scale national and regional projects across sectors such as water resources, transportation, agriculture, disaster management, and urban planning, while authoring nearly 50 peer-reviewed publications and serving as a reviewer and keynote speaker in many scientific forums. Recognized as a top researcher and elite member in Iran, his awards and honors reflect his excellence in both academic and applied contributions to geomatics and civil engineering. In conclusion, Dr. Ebrahimian Ghajari’s career demonstrates a unique integration of academic achievement, professional leadership, and impactful research, positioning him as a leading authority in advancing geomatics technologies for sustainable development and societal benefit.

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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.

Ebrahimian-Ghajari, Y., Alesheikh, A. A., Modiri, M., Hosnavi, R., & Nekouei, M. A. (2016). Modeling of seismic vulnerability of urban buildings in geographic information system environment: A case study in Babol, Iran.

 

Seyed Mostafa Mostafavi | Machine | Best Researcher Award

Dr. Seyed Mostafa Mostafavi | Machine | Best Researcher Award

Student, Imperial College London, United Kingdom

Dr. S. Mostafa Mostafavi emerges as a highly accomplished researcher and practitioner at the intersection of quantitative finance, machine learning, and communication systems. His rare blend of theoretical insight, practical implementation, and cross-disciplinary knowledge enables him to make meaningful contributions to both industry and academia. He has established himself as a thought leader in applying advanced machine learning techniques to financial markets and risk modeling, while also contributing to optimization and network theory in earlier phases of his career. His publication record and professional achievements suggest sustained innovation, technical mastery, and relevance.

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📚Publication 

🏁conclusion:

In conclusion, Dr. S. Mostafa Mostafavi is a compelling candidate for the Research for Best Researcher Award. His unique combination of academic excellence, industry leadership, and diverse research outputs positions him among the most impactful researchers in the fields of financial machine learning and quantitative analytics. With enhanced visibility in high-impact research communities and increased collaboration on global research initiatives, his future potential remains strong. Recognizing his contributions through this award would not only honor his achievements but also encourage further advancement in the critical nexus of AI.

Somayeh Zahabnazouri | Geoscience | Best Researcher Award

Dr. Somayeh Zahabnazouri | Geoscience | Best Researcher Award

Visiting Scholar, Utah State University. United States

Somayeh Zahabnazouri is currently serving as a Visiting Scholar at Utah State University. She holds a Ph.D. in Physical Geography from the University of Tehran and is presently pursuing a second Ph.D. in Earth and Environmental Science at the University of Bari. Her research interests span a broad range of environmental and geoscience topics, including climate change, wildfires, erosion modeling, geomorphology, river restoration, and remote sensing. She is proficient in a variety of technical tools and platforms such as ArcGIS, Google Earth Engine, Python, HEC-RAS, and SNAP, and has experience in pollen and grain size analysis. In addition to her research, she has over four years of teaching experience at Ferdowsi University and Shahid Bahonar University in Iran. Somayeh is a native speaker of Farsi, fluent in English, and has basic proficiency in Arabic and Italian.

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🏁conclusion:

Somayeh Zahabnazouri is a strong emerging researcher with a highly relevant and interdisciplinary background in environmental science and geomorphology. Her work addresses global environmental issues using modern geospatial and statistical tools. Her technical skills, teaching experience, and field/lab expertise make her a credible candidate for recognition.