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Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

Dean, Sivas University of Science and Technology, Turkey

Prof. Dr. Metin Zontul is a seasoned academic and researcher in the fields of machine learning, data mining, and intelligent systems, currently serving as Professor and Dean at the Faculty of Engineering and Natural Sciences, Sivas University of Science and Technology, Turkey. With over 30 years of academic experience, he has held various esteemed positions at several universities in Turkey and contributed significantly to national-level research projects, innovation in artificial intelligence, and academic leadership.

Publication Profile

Google Scholar

ORCID

🎓 Education Background

He earned his Ph.D. in Quantitative Methods in Business Administration (2004) from the Institute of Social Sciences, focusing his dissertation on clustering countries trading with Turkey using SOM-type artificial neural networks. He holds an M.Sc. in Computer-Aided Design, Manufacturing, and Programming (1996), where he analyzed local area network access protocols, and a B.Sc. in Computer Engineering (1993) from Middle East Technical University.

💼 Professional Experience

Prof. Zontul has held multiple academic ranks, starting as a Lecturer at Cumhuriyet University (1994–2005) and advancing to Assistant, Associate, and then Professor at institutions such as Istanbul Aydın University, Arel University, Ayvansaray University, and Topkapi University. He has been a key academic leader, serving as Dean and Department Chair across several faculties. Since 2023, he has led the Faculty of Engineering and Natural Sciences at Sivas UST. He also supervises graduate theses and collaborates on research with TUBITAK and other industry-linked projects.

🏆 Awards and Honors

Prof. Zontul has received Publication Incentive Awards from Istanbul Aydın University in 2014 and 2016 for his scholarly contributions. He is a former member of IEEE and holds a 2024 patent for a Personnel Assignment and Routing System related to unit failure and maintenance operations.

🔬 Research Focus

His research interests span machine learning, deep learning, data mining, signal processing, natural language processing, and intelligent systems. He has contributed extensively to the scientific community through 25+ peer-reviewed journal articles, 20+ conference papers, and collaborative projects involving academia and industry. His supervision of numerous theses and his involvement in over 30 national research projects reflect his commitment to practical and academic advancements in AI.

🔚 Conclusion

Prof. Dr. Metin Zontul stands as a multifaceted academician blending research, leadership, and innovation. His significant contributions to AI, education, and national research initiatives have cemented his reputation as a leading scholar in his field.

📚 Top Publications 

  1. Application of artificial intelligence neural network modeling to predict the generation of domestic, commercial and construction wastes (2021)
    Journal: Waste Management & Research
    Cited by: 92
    Co-authors: G. Coskuner, M.S. Jassim, S. Karateke

  2. Comparative performance analysis of support vector regression and artificial neural network for prediction of municipal solid waste generation (2022)
    Journal: Waste Management & Research
    Cited by: 49
    Co-authors: M.S. Jassim, G. Coskuner

  3. Urban bus arrival time prediction: A review of computational models (2013)
    Journal: International Journal of Recent Technology and Engineering (IJRTE)
    Cited by: 123
    Co-author: M. Altinkaya

  4. Measuring the efficiency of telecommunication sectors of OECD countries using data envelopment analysis (2005)
    Journal: CU Journal of Economics and Administrative Sciences
    Cited by: 41
    Co-authors: O. Kaynar, H. Bircan

  5. Wind speed forecasting using reptree and bagging methods in Kirklareli-Turkey (2013)
    Journal: Journal of Theoretical and Applied Information Technology
    Cited by: 35
    Co-authors: F. Aydin, G. Dogan, S. Sener, O. Kaynar

  6. The prediction of the ZnNi thickness and Ni% of ZnNi alloy electroplating using a machine learning method (2021)
    Journal: Transactions of the IMF
    Cited by: 34
    Co-authors: R. Katirci, H. Aktas

  7. A smart and mechanized agricultural application: From cultivation to harvest (2022)
    Journal: Applied Sciences
    Cited by: 31
    Co-authors: F. Kiani, G. Randazzo, I. Yelmen, A. Seyyedabbasi, S. Nematzadeh, F.A. Anka, et al.

 

 

Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

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