Assist. Prof. Dr. Hossein Bagherpour, Department of Biosystems Engineering, Bu-Ali Sina Universit, Iran
Dr. Hossein Bagherpour is an accomplished Assistant Professor in the Department of Biosystems Engineering at Bu-Ali Sina University, where he has served since 2013. Holding a Ph.D. and M.Sc. in Biosystems and Agricultural Machinery Engineering from Tarbiat Modares University and a B.Sc. in Mechanical Engineering from the University of Tehran, his interdisciplinary expertise bridges advanced engineering with agricultural innovation. Dr. Bagherpour is a leading researcher in the application of artificial intelligence and machine vision in precision agriculture, with a focus on plant disease detection, crop quality assessment, and robotic harvesting. He has supervised multiple Ph.D. and M.Sc. theses on deep learning, image processing, and AI-driven diagnostics for crops like rose, wheat, hazelnut, and quince. His contributions significantly advance smart farming technologies, offering solutions for enhanced productivity and sustainable agriculture in small and large-scale systems.
Professional Profile:
GOOGLE SCHOLAR
ORCID
Summary of Suitability for Best Researcher Award – Dr. Hossein Bagherpour
Dr. Hossein Bagherpour is an exemplary candidate for the Best Researcher Award, recognized for his pioneering work at the intersection of biosystems engineering, artificial intelligence, and precision agriculture. As an Assistant Professor at Bu-Ali Sina University since 2013, Dr. Bagherpour has made significant contributions to the development and application of intelligent systems in agricultural automation and food quality assessment.
🎓 Education
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🧪 Ph.D. in Biosystems Engineering – Tarbiat Modares University, Tehran, Iran
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🚜 M.Sc. in Agricultural Machinery Engineering – Tarbiat Modares University, Tehran, Iran
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⚙️ B.Sc. in Mechanical Engineering (Design of Machinery) – University of Tehran, Tehran, Iran
🏢 Work Experience
🏆 Achievements & Contributions
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📊 Supervised numerous Ph.D. and M.Sc. theses focusing on AI, deep learning, and smart agricultural systems
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🤖 Developed algorithms for robotic harvesting, crop disease detection, and quality inspection using machine learning and computer vision
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📚 Published multiple research papers (see Google Scholar) in areas such as AI-based phenotyping, intelligent sensors, and agricultural robotics
🎖 Awards & Honors
Publication Top Notes:
Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method
Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field
Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases
Detection of different adulteration in cinnamon powder using hyperspectral imaging and artificial neural network method
Design, Construction, and Evaluation of a Precision Vegetable Reaper to Use in Small Plots
A New Method to Optimize Deep CNN Model for Classification of Regular Cucumber Based on Global Average Pooling