Ilkay Cinar - Artificial intelligence - Best Researcher Award

Selcuk University - Turkey

AUTHOR PROFILE

SUMMARY

İlkay Çınar is a dynamic assistant professor and AI researcher dedicated to harnessing the power of artificial intelligence for practical solutions in agriculture, healthcare, and safety systems. Through academic excellence, research innovation, and committed mentorship, he continues to shape both technology and the minds that will drive its future.

EARLY ACADEMIC PURSUITS

İlkay Çınar began his academic journey in computer and electronics systems education, earning dual bachelor's degrees from Selçuk University in 2012 and 2018. His foundational years were marked by a growing fascination with artificial intelligence and image processing. He continued to explore machine learning in applied domains through his master’s research, focusing on classifying rice varieties using AI. His doctoral work on semantic image inpainting using deep generative models established his early dedication to pushing the boundaries of machine learning in visual computing.

PROFESSIONAL ENDEAVORS

As an academic at Selçuk University’s Department of Computer Engineering, İlkay Çınar advanced through the ranks from lecturer to assistant professor. He taught both undergraduate and graduate courses such as Image Processing, Web Architecture, and Smart Factory Systems. His work also included administrative leadership, serving as Deputy Director of the Distance Education Center. Throughout, he contributed to national research projects, emphasizing AI’s real-world applications across industries.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Çınar’s research centers on deep learning, machine learning, and their applications in agriculture, healthcare, and industry. His prolific publication record—spanning from automatic quality control in food processing to the detection of eye diseases and diabetes—demonstrates a commitment to interdisciplinary innovation. He has explored CNN, LSTM, and hybrid models, often with a focus on feature optimization, transfer learning, and mobile deployment, making his research impactful beyond academic circles.

ACCOLADES AND RECOGNITION

İlkay Çınar has published extensively in high-impact journals such as Computers and Electronics in Agriculture, Biomedical Signal Processing and Control, and European Food Research and Technology. His scholarly output includes more than 25 peer-reviewed international journal articles, numerous conference proceedings, and authored book chapters. His expertise has been acknowledged through active participation in prestigious conferences and ongoing collaborative projects, including TUBITAK-funded studies.

IMPACT AND INFLUENCE

Dr. Çınar’s research contributes significantly to societal needs by addressing challenges like food safety, medical diagnostics, and industrial automation. His supervised theses involve real-world issues, such as workplace safety violations and disease detection, underlining his mentorship’s practical value. He is helping shape a new generation of AI practitioners capable of integrating technological innovations with community needs.

LEGACY AND FUTURE CONTRIBUTIONS

Looking forward, İlkay Çınar is poised to continue advancing the integration of AI in health, agriculture, and environmental monitoring. His interdisciplinary focus positions him as a key figure in expanding the real-world applicability of deep learning in Turkey and beyond. His work on smart agriculture, medical image analysis, and automated quality assessment will likely have lasting impacts on both research and industrial sectors

NOTABLE PUBLICATIONS

Title: Classification of rice varieties with deep learning methods
Authors: M. Koklu, I. Cinar, Y.S. Taspinar
Journal: Computers and Electronics in Agriculture

Title: Classification of rice varieties using artificial intelligence methods
Authors: I. Cinar, M. Koklu
Journal: International Journal of Intelligent Systems and Applications in Engineering

Title: Classification of Date Fruits into Genetic Varieties Using Image Analysis
Authors: M. Koklu, R. Kursun, Y.S. Taspinar, I. Cinar
Journal: Mathematical Problems in Engineering

Title: Classification and analysis of pistachio species with pre-trained deep learning models
Authors: D. Singh, Y.S. Taspinar, R. Kursun, I. Cinar, M. Koklu, I.A. Ozkan, H.N. Lee
Journal: Electronics

Title: Identification of Rice Varieties Using Machine Learning Algorithms
Authors: I. Cinar, M. Koklu
Journal: Journal of Agricultural Sciences (Tarım Bilimleri Dergisi)

Title: Classification of Raisin Grains Using Machine Vision and Artificial Intelligence Methods
Authors: I. Cinar, M. Koklu, S. Tasdemir
Journal: Gazi Mühendislik Bilimleri Dergisi (GMBD)

EARLY ACADEMIC PURSUITS

Jamin Rahman Jim's academic journey commenced with a Bachelor of Science degree in Computer Science and Engineering, with a major in Information Systems, from the American International University-Bangladesh. His exceptional academic performance, evidenced by a final grade of 3.96/4.00, was complemented by a thesis focusing on assessing Personalized Federated Learning Algorithms for Pattern Recognition Tasks.

PROFESSIONAL ENDEAVORS

Jamin Rahman Jim has established himself as a dedicated researcher in the field of artificial intelligence and machine learning. His roles as a Research Assistant at Deepchain Labs and subsequently as a Researcher at the Advanced Machine Intelligence Research Lab (AMIR Lab) reflect his commitment to advancing knowledge and contributing to cutting-edge research projects.

CONTRIBUTIONS AND RESEARCH FOCUS

With a focus on artificial intelligence and machine learning, Jamin Rahman Jim has made significant contributions to the field through his publications and projects. His research spans various domains, including the trustworthy metaverse, NLP-based sentiment analysis, deep learning for medical image segmentation, and user authentication and authorization in cybersecurity. Through preprints and published articles, he continues to explore innovative approaches and address challenges in the application of machine learning techniques.

IMPACT AND INFLUENCE

Jamin Rahman Jim's research has garnered attention within the academic community and beyond, as evidenced by his publications in reputable journals and his receipt of prestigious awards and grants. His work on generative AI in medical imaging, fusion-enhanced terrain detection, and explainable AI approaches has the potential to influence the development of AI systems in various domains, including healthcare, autonomous vehicles, and cybersecurity.

ACADEMIC CITES

Jamin Rahman Jim's publications in journals such as IEEE Access, Natural Language Processing Journal, and Computers and Electrical Engineering have been cited by fellow researchers, indicating the relevance and impact of his work. His research on generative AI in medical imaging, personalized federated learning algorithms, and lightweight human activity recognition frameworks has contributed to advancing knowledge in the field of artificial intelligence.

LEGACY AND FUTURE CONTRIBUTIONS

As Jamin Rahman Jim continues his academic and professional journey, his legacy lies in his dedication to advancing the field of artificial intelligence and machine learning. Through his ongoing research projects, publications, and collaborations, he aims to address critical challenges and contribute to the development of innovative AI solutions. His focus on generative AI in medical imaging underscores his commitment to leveraging AI for improved healthcare outcomes and societal impact.