Assoc. Prof. Dr. Nana Yaw Asabere | Big Data | Best Researcher Award

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Assoc. Prof. Dr. Nana Yaw Asabere | Big Data | Best Researcher Award 

Assoc. Prof. Dr. Nana Yaw Asabere | Accra Technical University | Ghana

Assoc. Prof. Dr. Nana Yaw Asabere is a distinguished Associate Professor of Computer Science and currently serves as the Dean of the Faculty of Applied Sciences at Accra Technical University, Ghana. With a career spanning nearly two decades, he has established himself as a leading scholar, researcher, and academic leader in the fields of computer science, information and communication technology, and artificial intelligence. His expertise lies in teaching, supervising research, advancing innovative methodologies, and contributing impactful scholarship to the global academic community. Recognized both locally and internationally, Prof. Asabere has played a pivotal role in shaping academic excellence, research visibility, and technological advancement in Ghana and beyond.

Professional Profile

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Summary of Suitability

Assoc. Prof. Dr. Nana Yaw Asabere  is a highly accomplished researcher and academic leader in the field of Computer Science, ICT, and IT, with significant contributions to teaching, research, innovation, and academic leadership. His strong academic background (B.Sc., M.Sc., Ph.D.) is complemented by international training and recognition, including a Chinese Government Scholarship for his Ph.D., where he developed and evaluated novel algorithms to address complex challenges in socially-aware recommendation systems.

Education

Assoc. Prof. Dr. Nana Yaw Asabere educational journey demonstrates a solid foundation and progressive specialization in computer science and ICT. He completed a Bachelor of Science in Computer Science at the Kwame Nkrumah University of Science and Technology in Ghana, followed by a Master of Science in Information and Communication Technologies at Aalborg University, Denmark. He was later awarded a prestigious scholarship from the Chinese Government through the Chinese Scholarship Council to pursue his Doctor of Philosophy in Computer Science at Dalian University of Technology, China. His doctoral work significantly advanced socially-aware recommendation systems for smart conferences, where he designed and evaluated multiple algorithms addressing complex computational challenges. This robust academic training has underpinned his innovative contributions to teaching and research.

Experience

With more than eighteen years of teaching and research experience, Assoc. Prof. Dr. Nana Yaw Asabere has contributed substantially to both undergraduate and postgraduate education. He has held several leadership positions at Accra Technical University, including Head of the Department of Computer Science, Director of the Directorate of Research, Innovation, Publication and Technology Transfer, and Coordinator for Non-Tertiary and Professional Programmes. His academic leadership spans over six years, during which he has fostered innovation, research visibility, and institutional development. Beyond administration, he remains actively engaged in curriculum design, research mentorship, and the dissemination of knowledge through lectures, conferences, and international collaborations.

Research Interests

Assoc. Prof. Dr. Nana Yaw Asabere research focuses on cutting-edge areas in computer science, including software engineering, artificial intelligence, big data analytics, social recommender systems, data science, and ICT integration in education. His scholarly work has combined theoretical depth with practical applications, particularly in advancing recommendation systems for smart environments and applying AI in educational technologies such as e-learning and m-learning. He has authored and co-authored numerous high-impact journal articles and conference papers, many of which have been indexed in globally recognized databases such as Web of Science and Scopus. His contributions continue to shape emerging discussions in intelligent systems and their applications in education and society.

Awards

Assoc. Prof. Dr. Nana Yaw Asabere has received multiple recognitions for his innovative research and impactful contributions. His work on socially-aware recommendation algorithms earned him a Best Paper Award at a leading IEEE international conference on ubiquitous intelligence and computing. He has also received another Best Paper Award at a major IEEE international conference on adaptive science and technology. In addition to these honors, his research visibility, editorial contributions, and active involvement as a peer reviewer for top-tier journals and conferences reflect his standing as an influential researcher within the global academic community.

Publication Top Notes

An integrated multi-scale context-aware network for efficient desnowing

Improving Counseling Sessions Through an Interactive Web-Based Application in the Context of Higher Education

Acceptability and Feasibility of a Pilot Multifamily Group Intervention for Fostering Positive Racial Identity

Nighttime Object Detection with Denoising Diffusion-Probabilistic Models

Conclusion

Assoc. Prof. Dr. Nana Yaw Asabere embodies the qualities of an outstanding researcher, educator, and leader in computer science and ICT. His contributions extend beyond academic publications to institutional leadership, mentoring, and advancing technological innovation in education. With significant citations, impactful research, international recognition, and demonstrated excellence in teaching and leadership, he is a strong candidate for recognition through a Best Researcher Award. His work continues to inspire young scholars, advance computational sciences, and promote the integration of technology for societal benefit.

 

Hemad Zareiforoush | Machine Learning | Best Academic Researcher Award

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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.