Dr. Hemad Zareiforoush | Machine Learning | Best Academic Researcher Award

Associate Professor at University of Guilan, Rasht, Iran

Dr. Hemad Zareiforoush is an Assistant Professor at the Department of Biosystems Engineering, University of Guilan, Rasht, Iran, where he has been contributing to both academic and practical advancements in biosystems engineering since 2015. With a focus on agricultural machinery, automation, and quality inspection systems, his work bridges engineering and food science, particularly in areas like computer vision, image processing, and renewable energy applications. His research is highly interdisciplinary, combining mechanical engineering principles with computational intelligence for improving the agricultural industry’s efficiency.

Profile

Google Scholar

Education

Dr. Zareiforoush’s educational background is robust, with a PhD in Mechanical and Biosystems Engineering from Tarbiat Modares University in Tehran, Iran, completed in 2014. His academic excellence is evident in his GPA of 17.84 out of 20. He earned his MSc in Mechanical Engineering of Agricultural Machinery at Urmia University in 2010, where he graduated with a remarkable GPA of 19.29 out of 20. Earlier, Dr. Zareiforoush obtained his BSc in the same field from Urmia University in 2007, graduating with a GPA of 15.75 out of 20. He also attended a specialized governmental high school for excellent pupils, where he focused on mathematics and physics, graduating with a GPA of 18.71 out of 20.

Experience

Since joining the University of Guilan in 2015, Dr. Zareiforoush has been teaching various courses, including Engineering Properties of Food and Agricultural Products, Renewable Energy, and Measurement and Instrumentation Principles. His practical experience spans various engineering disciplines, with a particular emphasis on instrumentation, automation in agriculture, and food quality monitoring. Notably, his research has led to the development of innovative systems for rice quality inspection using computer vision and fuzzy logic. Additionally, he has been involved in numerous projects related to agricultural machinery, renewable energy, and automation for optimizing food production processes.

Research Interests

Dr. Zareiforoush’s research interests lie at the intersection of biosystems engineering, computational intelligence, and food science. He is particularly interested in computer vision applications for food quality inspection, using advanced image processing techniques to enhance product quality and safety. His work also explores hyperspectral imaging and spectroscopy for monitoring the quality of food materials. Another key area of his research is the application of machine learning algorithms for modeling and classifying food products based on their quality attributes. Additionally, he is involved in renewable energy applications in agriculture, focusing on solar-assisted drying systems and energy-efficient food processing methods.

Awards

Dr. Zareiforoush has received several prestigious awards throughout his academic career. He was honored with the Iran Ministry of Science, Research, and Technology Scholarship in 2012 and the National Elite Scholarship by the Iran National Foundation for Elites (INFE) in 2011. His exceptional academic performance earned him the title of “Best Student” at Urmia University in 2009. Additionally, he has been recognized as a “Talented Student” at Tarbiat Modares University and ranked 1st among MSc students in his department.

Publications

Dr. Zareiforoush has published several influential papers in high-impact journals. Some of his notable publications include:

Bakhshipour, A., Zareiforoush, H., Bagheri, I. (2020). Application of decision trees and fuzzy inference system for quality classification and modeling of black and green tea based on visual features. Journal of Food Measurement and Characterization, 14: 1402–1416, Cited by: 43.

Bakhshipour, A., Zareiforoush, H., Bagheri, I. (2020). Development of a fuzzy model for differentiating peanut plant from broadleaf weeds using image features. Plant Methods, 16:153, Cited by: 25.

Bakhshipour, A., Zareiforoush, H., Bagheri, I. (2021). Mathematical and intelligent modeling of stevia (Stevia Rebaudiana) leaves drying in an infrared-assisted continuous hybrid solar dryer. Food Science & Nutrition (JCR), 9(1), 532-543, Cited by: 12.

Zareiforoush, H., Minaei, S., Alizadeh, M.R., Banakar, A. (2016). Design, Development, and Performance Evaluation of an Automatic Control System for Rice Whitening Machine Based on Computer Vision and Fuzzy Logic. Computers and Electronics in Agriculture, 124: 14-22, Cited by: 67.

Soodmand-Moghaddam, S., Sharifi, M., Zareiforoush, H. (2020). Mathematical modeling of lemon verbena leaves drying in a continuous flow dryer equipped with a solar pre-heating system. Quality Assurance and Safety of Crops & Foods, 12(1): 57-66, Cited by: 30.

Zareiforoush, H., Minaei, S., Alizadeh, M.R., Banakar, A. (2015). Qualitative Classification of Milled Rice Grains Using Computer Vision and Metaheuristic Techniques. Journal of Food Science and Technology (Springer), 53(1): 118-131, Cited by: 45.

Zareiforoush, H., Komarizadeh, M.H., Alizadeh, M.R. (2010). Effects of crop-screw parameters on rough rice grain damage in handling with a horizontal screw auger. Journal of Food, Agriculture and Environment, 8(3): 132-138, Cited by: 19.

Conclusion

Dr. Hemad Zareiforoush’s academic and professional contributions significantly impact the fields of biosystems engineering, food science, and agricultural machinery. His work in developing intelligent systems for quality inspection and automation has improved agricultural productivity and food safety. His expertise in computational techniques, including fuzzy logic and machine learning, continues to shape the future of smart farming and food processing. With numerous awards, highly cited publications, and a track record of excellence, Dr. Zareiforoush is a leading figure in his field.