Education
Dr. Farhad Soleimanian Gharehchopogh holds a Ph.D. in Computer Science, specializing in Software Engineering from Urmia University, Iran. His doctoral research focused on advanced optimization techniques and their applications in artificial intelligence. Prior to his Ph.D., he completed a Master of Science in Software Engineering at Islamic Azad University, Tabriz Branch, where he developed a strong foundation in programming, data structures, and algorithm design. He earned his Bachelor of Science in Computer Science from Islamic Azad University, Urmia Branch, where he first explored his interest in computational intelligence. His academic journey has been characterized by a consistent focus on deepening his understanding of complex computational systems.
Professional Experience
Dr. Farhad Soleimanian Gharehchopogh has held various academic positions throughout his career, contributing to the growth of computer science education and research. He has served as an Assistant Professor at Islamic Azad University, Urmia Branch, where he taught undergraduate and graduate courses in software engineering and computer science. In addition to teaching, he has supervised numerous master’s and Ph.D. students, guiding their research in areas like machine learning and optimization algorithms. He has also collaborated with international researchers on various projects, aiming to solve real-world problems using advanced computational methods. His professional experience is marked by a commitment to fostering innovation in both academic and practical applications of computer science.
Research Interest
Dr. Soleimanian’s research interests are centered around machine learning, artificial intelligence, and computational optimization. He is particularly interested in developing new algorithms for data mining, evolutionary computing, and swarm intelligence. His work often explores how optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, can be applied to solve complex problems in various fields. Additionally, he is passionate about deep learning and its applications in pattern recognition, natural language processing, and image analysis. Dr. Soleimanian continually seeks to advance the field through innovative research, aiming to bridge the gap between theoretical concepts and practical implementations.
Research Skills
Dr. Farhad Soleimanian Gharehchopogh possesses a wide array of research skills that make him a leader in computational intelligence and software engineering. He has extensive experience in developing and implementing optimization algorithms, leveraging his expertise in evolutionary computing and metaheuristics. Proficient in programming languages such as Python, MATLAB, and C++, he applies these skills to simulate and analyze complex models. Dr. Soleimanian is also skilled in statistical analysis and data visualization, enabling him to derive meaningful insights from large datasets. His ability to collaborate effectively with other researchers and his strong analytical mindset have allowed him to make significant contributions to his field.
Awards and Honors
Dr. Soleimanian’s excellence in research and education has been recognized with several awards and honors throughout his career. He has received accolades for his high-quality research papers presented at international conferences and published in peer-reviewed journals. His contributions to the field have been acknowledged with best paper awards and recognition from academic societies. He has also been honored for his outstanding teaching and mentoring, guiding students towards academic and professional success. Dr. Soleimanian’s dedication to advancing computer science and his commitment to academic excellence have made him a recipient of numerous prestigious awards, highlighting his impact in both research and education.
Conclusion
Dr. Farhad Soleimanian Gharehchopogh is a strong candidate for the Best Researcher Award, given his extensive research output, mentorship of graduate students, and recognition among the top-cited scientists globally. His consistent contributions to the academic and research community, particularly in computer engineering, make him well-suited for this award. Addressing the minor areas for improvement, such as updating student mentorship records and highlighting recent publications, would further solidify his application.
Publications Top Notes
- Recent applications and advances of African Vultures Optimization Algorithm
Authors: AG Hussien, FS Gharehchopogh, A Bouaouda, S Kumar, G Hu
Journal: Artificial Intelligence Review 57 (12), 1-51
Year: 2024
Citations: Not specified
- An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer
Authors: FA Özbay, E Özbay, FS Gharehchopogh
Journal: CMES-Computer Modeling in Engineering & Sciences 141 (2)
Year: 2024
Citations: Not specified
- Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems
Authors: M Abdel-Salam, G Hu, E Çelik, FS Gharehchopogh, IM El-Hasnony
Journal: Computers in Biology and Medicine 179, 108803
Year: 2024
Citations: 6
- A hybrid principal label space transformation-based ridge regression and decision tree for multi-label classification
Authors: SHS Ebrahimi, K Majidzadeh, FS Gharehchopogh
Journal: Evolving Systems, 1-37
Year: 2024
Citations: Not specified
- Multifeature Fusion Method with Metaheuristic Optimization for Automated Voice Pathology Detection
Authors: E Özbay, FA Özbay, N Khodadadi, FS Gharehchopogh, S Mirjalili
Journal: Journal of Voice
Year: 2024
Citations: Not specified
- A Quasi-Oppositional Learning-based Fox Optimizer for QoS-aware Web Service Composition in Mobile Edge Computing
Authors: RH Sharif, M Masdari, A Ghaffari, FS Gharehchopogh
Journal: Journal of Grid Computing 22 (3), 64
Year: 2024
Citations: Not specified
- A novel offloading strategy for multi-user optimization in blockchain-enabled Mobile Edge Computing networks for improved Internet of Things performance
Authors: AM Rahmani, J Tanveer, FS Gharehchopogh, S Rajabi, M Hosseinzadeh
Journal: Computers and Electrical Engineering 119, 109514
Year: 2024
Citations: 5
- An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer
Authors: H Asgharzadeh, A Ghaffari, M Masdari, FS Gharehchopogh
Journal: Journal of Bionic Engineering 21 (5), 2658-2684
Year: 2024
Citations: 2
- Visualization and classification of mushroom species with multi-feature fusion of metaheuristics-based convolutional neural network model
Authors: E Özbay, FA Özbay, FS Gharehchopogh
Journal: Applied Soft Computing 164, 111936
Year: 2024
Citations: 1
- A software defect prediction method using binary gray wolf optimizer and machine learning algorithms
Authors: H Wang, B Arasteh, K Arasteh, FS Gharehchopogh, A Rouhi
Journal: Computers and Electrical Engineering 118, 109336
Year: 2024
Citations: 1