Assistant Professor at Hamadan University of Medical Sciences, Iran
Dr. Mansoorian is a seasoned academic and researcher with a solid foundation in computer engineering and a strong emphasis on artificial intelligence and machine learning. Over the years, he has built a reputation for his work in optimization algorithms, intelligent systems, and IoT-based solutions, integrating computational techniques with real-world applications. With an educational journey rooted in Iran’s prestigious universities and significant contributions in both academia and industry, Dr. Mansoorian has emerged as a notable figure in the fields of AI and computer science, recognized for both his scholarly work and practical innovations.
Profile
Scopus
Education
Dr. Mansoorian began his academic journey with a Bachelor’s degree in Computer Engineering–Software from the Islamic Azad University, Dezful Branch, Iran, where he graduated in 2005. He then pursued his Master of Science in Computer Engineering–Artificial Intelligence at the Science and Research Branch of Islamic Azad University in Tehran, completing it in 2009. Driven by a keen interest in optimization and AI, he earned his Ph.D. in the same field from the Science and Research Branch, IAU, Tehran, in 2017. His doctoral research focused on enhancing bio-inspired optimization algorithms and applying them to complex computational problems, setting the stage for a promising academic and research career.
Profession
Professionally, Dr. Mansoorian has held multiple academic positions, including serving as an assistant professor and faculty member at the Islamic Azad University, Ahvaz Branch, where he played a vital role in research, teaching, and administrative leadership. He has also served as a lecturer in various other universities, teaching a broad spectrum of courses in AI, computer architecture, neural networks, and programming. His career reflects a balance between academic instruction and research leadership, with several years dedicated to advising graduate students, managing university projects, and engaging in interdisciplinary collaborations. Dr. Mansoorian’s professional experience is marked by a commitment to integrating AI with real-world engineering systems, such as smart home devices and energy optimization tools.
Research
Dr. Mansoorian’s research interests lie at the intersection of artificial intelligence, machine learning, IoT systems, and bio-inspired optimization. He has extensively explored heuristic and metaheuristic algorithms like Genetic Algorithms, Particle Swarm Optimization, and Ant Colony Optimization, applying these to diverse domains including energy efficiency, image processing, and disease detection. His interdisciplinary focus also extends to AI-based systems for smart healthcare and environmental monitoring. Notably, his recent projects involve the development of fuzzy systems, ensemble learning methods, and novel hybrid algorithms designed to solve NP-hard problems with enhanced computational efficiency and accuracy.
Awards
Throughout his career, Dr. Mansoorian has been recognized for his contributions through multiple awards and honors. He has received acknowledgments for his research papers at international conferences and has been a prominent participant in academic competitions related to intelligent systems. In addition, he has received university-level awards for excellence in teaching and innovation. These accolades highlight his dual strength as an educator and a research innovator.
Publications
Among his scholarly contributions, Dr. Mansoorian has authored and co-authored several impactful publications. Notable works include: (1) “A new hybrid method for feature selection based on genetic algorithm and SVM,” published in Applied Soft Computing (2019), cited 87 times; (2) “Hybrid feature selection based on enhanced genetic algorithm and fuzzy logic for heart disease diagnosis,” published in Computer Methods and Programs in Biomedicine (2020), cited 53 times; (3) “Fuzzy decision-making system based on ensemble learning models for energy consumption prediction,” published in Journal of Building Engineering (2021), cited 42 times; (4) “Internet of Things-based smart home energy management using machine learning,” published in Energy and Buildings (2020), cited 60 times; (5) “Optimized hybrid deep learning model for liver disease detection using ensemble CNN-LSTM,” published in Expert Systems with Applications (2022), cited 31 times; (6) “A novel IoT framework for smart irrigation using fuzzy controllers,” published in Computers and Electronics in Agriculture (2021), cited 26 times; and (7) “An enhanced ACO-based clustering protocol for wireless sensor networks,” published in Ad Hoc Networks (2018), cited 78 times. These publications reflect his wide-ranging research endeavors and their influence in the academic community.
Conclusion
In conclusion, Dr. Mansoorian exemplifies the qualities of an outstanding nominee for any award recognizing innovation and excellence in computer science and artificial intelligence. With a solid academic foundation, prolific research output, and a dedication to applying intelligent systems in practical contexts, he continues to push the boundaries of technological advancement. His commitment to mentorship, research leadership, and real-world impact positions him as a transformative figure in AI and computational sciences. He is highly deserving of recognition for his ongoing contributions to the global scientific community.