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Assoc. Prof. Dr.Javad Rahebi | Thermodynamics Award | Best Researcher Award

Assoc. Prof. Dr.Javad Rahebi | istanbul topkapi university | Turkey

Javad Rahebi is an accomplished academic and researcher in the field of Electric and Electronic Engineering. He obtained his Ph.D. from Gazi University, Turkey, in 2015, specializing in digital signal processing and communication systems. Currently an Assistant Professor at Istanbul Topkapi University, he has previously held faculty positions at several institutions, including Altinbas University and the University of Turkish Aeronautical Association. Rahebi is known for his contributions to the integration of artificial intelligence in engineering applications, focusing on optimization methods. His commitment to education is reflected in his extensive teaching experience across multiple universities, where he has delivered courses in MATLAB, Simulink, and digital image processing. He actively engages in research collaborations, publishing numerous papers in prestigious journals, and serves as a keynote speaker at various conferences, enhancing his reputation in the academic community.

Professional Profile:

Google Scholar:

Scopus

Summary of Suitability for Award:

Javad Rahebi’s profile exemplifies the qualities of a distinguished researcher worthy of the “Best Researcher Awards.” With a Ph.D. in Electric and Electronic Engineering, he has specialized in areas critical to modern technology, such as digital signal processing and artificial intelligence. His active involvement in academia, particularly as an Assistant Professor, highlights his commitment to education and knowledge dissemination. Rahebi’s research output is impressive, with numerous publications in reputable journals that contribute significantly to the fields of optimization and communication systems. His role as a keynote speaker at various conferences further establishes him as a thought leader in his domain. Rahebi’s innovative approaches to integrating AI into engineering applications demonstrate his potential to impact both research and industry positively.

🎓Education:

Javad Rahebi pursued his academic journey with a strong focus on engineering. He earned his B.S. in Communication Engineering from Azad University of Oromieh, Iran, in 2005. Building on this foundation, he obtained his M.Sc. in Communication Engineering from Sadjad University of Technology, Mashhad, Iran, in 2009. His quest for knowledge culminated in a Ph.D. degree in Electric and Electronic Engineering from Gazi University, Turkey, between 2011 and 2015. During his doctoral studies, Rahebi specialized in digital signal processing, which laid the groundwork for his future research endeavors. His educational background is complemented by relevant coursework in digital image processing, artificial intelligent systems, and optimization methods, equipping him with a robust skill set that supports his current research and teaching activities.

🏢Work Experience:

Javad Rahebi has built a distinguished academic career with extensive teaching and research experience. Since September 2020, he has served as an Assistant Professor at Istanbul Topkapi University, where he imparts knowledge in various engineering disciplines. Prior to this role, he was an Assistant Professor at Altinbas University from September 2019 to August 2020 and the University of Turkish Aeronautical Association from October 2015 to August 2019. His professional experience extends to practical applications of engineering principles, having worked with FİGES A.Ş. and Havelsan in Ankara, Turkey, focusing on signal processing and teaching MATLAB and Simulink. Rahebi has also contributed to curriculum development by teaching optimization, artificial neural networks, and MATLAB courses across multiple universities. His diverse experience equips him to bridge theoretical concepts with real-world applications, enhancing the educational experience of his students.

🏅Awards:

Throughout his academic career, Javad Rahebi has garnered recognition for his contributions to engineering and education. He has been actively involved in organizing international conferences, such as the Imeset International Conference (IMESET), highlighting his commitment to advancing academic discourse. Rahebi’s work has also earned him opportunities as a keynote speaker, notably presenting on “Optimization Methods in Engineering” at Rajalakshmi Engineering College in Chennai, India, in April 2018. His publications in high-impact journals reflect his research excellence, showcasing innovative applications of artificial intelligence in engineering. The acknowledgment of his research contributions is evidenced by the citations and collaborations with esteemed scholars in the field. Rahebi’s dedication to his profession and his students is further exemplified by his continuous efforts to enhance educational methodologies and foster a collaborative research environment.

🔬Research Focus:

Javad Rahebi’s research primarily revolves around signal processing, communication systems, and the application of artificial intelligence in engineering. His work encompasses the development and optimization of algorithms for various applications, including deep learning techniques for image processing and cybersecurity. Rahebi has contributed significantly to the field of optimization methods, exploring swarm intelligence algorithms, such as the Fishier Mantis Optimizer and Harris Hawks Optimization, to enhance the efficiency of complex systems. His research also extends to the techno-economical operation of microgrids, focusing on real-time decision-making under uncertainties. Additionally, he investigates the integration of machine learning with traditional engineering methodologies to improve diagnostic processes in medical applications, such as colon cancer detection. Through his interdisciplinary approach, Rahebi aims to bridge the gap between theoretical research and practical applications, contributing to advancements in both engineering and technology.

Publication Top Notes:

  • Title: A new approach to optic disc detection in human retinal images using the firefly algorithm
    Citations: 72
  • Title: Retinal blood vessel segmentation with neural network by using gray-level co-occurrence matrix-based features
    Citations: 67
  • Title: Skin lesion segmentation method for dermoscopy images using artificial bee colony algorithm
    Citations: 65
  • Title: Multilevel thresholding of images with improved Otsu thresholding by black widow optimization algorithm
    Citations: 60
  • Title: A Study of Deep Neural Network Controller‐Based Power Quality Improvement of Hybrid PV/Wind Systems by Using Smart Inverter
    Citations: 58

 

 

Assoc. Prof. Dr.Javad Rahebi | Thermodynamics Award | Best Researcher Award

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