Yasas Gamagedara | Soil Spectroscopy | Research Excellence Award

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Shahbaz Khan | Agronomy and Horticulture | Best Researcher Award

Dr. Shahbaz Khan | Agronomy and Horticulture | Best Researcher Award

Horticulturist in Hainan University, Pakistan

Dr. Shahbaz Khan holds a PhD in Agronomy  from Huazhong Agricultural University, China, with research focused on improving rapeseed growth, yield, and lodging resistance, and a Master’s degree in Agronomy from Sindh Agriculture University, Pakistan, specializing in wheat performance under saline conditions. His academic training covers advanced crop production, crop modeling, plant physiology, multivariate statistics, soil fertility, irrigation, weed management, and sustainable agriculture. He has over a decade of professional experience as a Research Officer  and Horticulturist with the Directorate of Agriculture Research, Government of Balochistan, Pakistan. His research interests include plant physiological responses to abiotic stress, tillage and cultivation techniques, photosynthesis, plant water relations, water use efficiency, and yield enhancement strategies. He has led and contributed to international research projects on dryland farming, desertification control, wastewater biopurification, and nutrient management, published conference papers, and holds two authorized patents on agricultural machinery. Dr. Khan is actively engaged in teaching, serves as an Associate Editor for a special issue in Frontiers in Plant Science, and reviews for numerous high-impact international journals in agronomy, soil science, and environmental sciences.

Citation Metrics (Scopus)

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Nadia Saadati | Sustainable Agriculture (precision agriculture) | Women Researcher Award

Mrs. Nadia Saadati | Sustainable Agriculture (precision agriculture) | Women Researcher Award

Mrs. Nadia Saadati | University of Mohaghegh Ardabili | Iran

Mrs. Nadia Saadati is a Ph.D. candidate in Agricultural Mechanization Engineering (Systems Analysis and Management) at the University of Mohaghegh Ardabili, Iran, with an outstanding focusing her doctoral research on the detection of infected corn leaves using image processing and deep learning. She holds both M.Sc. and B.Sc. degrees in Agricultural Mechanization Engineering from the same university, specializing in remote sensing, precision agriculture, and mechanization systems. Her research expertise spans agricultural innovation, technology transfer strategies, mechanization development, and smart agriculture applications. She has filed and registered seven patents in Iran covering agricultural machinery innovations such as snow blowers, garlic and lentil harvesters, potato harvesters, and crop evaluation systems, reflecting her strong inventive and engineering capability. Actively engaged in applied research, she leads projects on saffron quality assessment using electronic noses and bean characterization through spectrometry. As a technology manager and R&D member at Adaptive AgroTech and the University of Mohaghegh Ardabili’s Technology Growth Center, she contributes to developing practical agricultural technologies. She is also a patent evaluator at Ardabil Science and Technology Park and the founder and vice chairman of Arda Sanat Sabz Company, advancing sustainable mechanization solutions. Her professional memberships include WIIPA Middle East, ISIC, and the Iranian Society of Agricultural Machinery Engineering and Mechanization, along with editorial roles in the Nobel and Farmtech journals. Internationally certified, she has completed courses from WIPO, FAO, UN Women, HP LIFE, and the University of Leeds in AI, data science, programming, and agricultural innovation. She has received multiple awards, including the Best Young Inventor Award from WIPO and WIIPA and recognition as the top student at her university. Mrs. Saadati has published 10 research papers, with over 120 citations and an h-index of 6, demonstrating her growing impact in agricultural mechanization, AI in farming systems, and technology-driven sustainability. Her academic, inventive, and professional journey reflects a commitment to transforming agriculture through intelligent mechanization and interdisciplinary innovation.

Profiles:  Scopus Orcid | Google Scholar 

Featured Publications

Saadati, N., & Najar, A. (2025). A hybrid artificial neural network–bee colony algorithm for developing a machine vision system to differentiate between two types of weeds. Biosystems Engineering and Renewable Energies.

Saadati, N., & Ahmadi Teshnizi, M. (2025). Development of a computer vision system for classifying leaves of five distinct tree species. Biosystems Engineering and Renewable Energies.

Saadati, N., Pourdarbani, R., Sabzi, S., & Hernandez-Hernandez, J. L. (2024). Identification of armyworm-infected leaves in corn by image processing and deep learning. Acta Technologica Agriculturae, 27(2), 103–110.