Ahmet Kayabaşı| Artificial Intelligence | Best Researcher Award

Prof. Dr. Ahmet Kayabaşı | Artificial Intelligence | Best Researcher Award

Professor | Karamanoglu Mehmetbey University | Turkey

Prof. Dr. Ahmet Kayabaşı is a distinguished academic in electrical-electronics engineering with expertise in artificial intelligence, antennas, biomedical signal processing, image processing, fuzzy logic, and power electronics. He earned his PhD in Electrical-Electronics Engineering from Selcuk University and has since built a strong academic career combining teaching, research, and leadership. His professional experience includes serving as Head of Department, Director of the Institute of Graduate Studies, and Senate Member, along with mentoring numerous MSc and PhD students. His research interests span interdisciplinary fields, applying advanced AI techniques in UAV swarm algorithms, smart agriculture, biomedical diagnostics, and energy-efficient power systems. He has been actively involved in TÜBİTAK and institutional projects, contributing to impactful solutions for both academia and industry. Recognized for his excellence, he has received awards such as Best Presenter Award at ICAT and has played vital roles in academic conferences and scientific communities. His research skills include developing intelligent systems, applying machine learning to engineering challenges, and designing novel antenna and biomedical applications. He has published widely in leading international journals indexed in IEEE, Scopus, and Web of Science, with notable contributions in Applied Thermal Engineering, Swarm and Evolutionary Computation, and Computers and Electronics in Agriculture. His academic excellence is reflected in 609 citations by 522 documents, 47 publications, and an h-index of 13.

Profile: Google Scholar | Scopus | ORCID

Featured Publications

  1. Sabanci, K., Kayabasi, A., & Toktas, A. (2017). Computer vision‐based method for classification of wheat grains using artificial neural network. Journal of the Science of Food and Agriculture, 97(8), 2588–2593.

  2. Yigit, E., Sabanci, K., Toktas, A., & Kayabasi, A. (2019). A study on visual features of leaves in plant identification using artificial intelligence techniques. Computers and Electronics in Agriculture, 156, 369–377.

  3. Kayabasi, A., Toktas, A., Yigit, E., & Sabanci, K. (2018). Triangular quad-port multi-polarized UWB MIMO antenna with enhanced isolation using neutralization ring. AEU-International Journal of Electronics and Communications, 85, 47–53.

  4. Sabanci, K., Toktas, A., & Kayabasi, A. (2017). Grain classifier with computer vision using adaptive neuro‐fuzzy inference system. Journal of the Science of Food and Agriculture, 97(12), 3994–4000.

  5. Yildiz, B., Aslan, M. F., Durdu, A., & Kayabasi, A. (2024). Consensus-based virtual leader tracking swarm algorithm with GDRRT*-PSO for path-planning of multiple-UAVs. Swarm and Evolutionary Computation, 88, 101612.

Barat Barati | Artificial Intelligence | Research Impact Award

Assist. Prof. Dr. Barat Barati | Artificial Intelligence | Research Impact Award

Medical Physics | Shoushtar Faculty of Medical Sciences | Iran

Assist. Prof. Dr. Barat Barati is a distinguished academician and researcher specializing in radiotherapy, artificial intelligence (AI), and computational simulation, with a career dedicated to advancing healthcare diagnostics and treatment through innovative research and teaching. Currently serving as a faculty member at Shoushtar Faculty of Medical Sciences, he integrates deep learning models with biomedical signal processing to address challenges in medical sciences, particularly brain tumor diagnosis and classification. He earned his doctoral degree with a specialization in artificial intelligence and simulation methods, where his PhD research introduced novel approaches by combining machine learning algorithms with Monte Carlo simulation tools such as MCNP, significantly advancing medical physics and diagnostic imaging. With a strong foundation in physics, mathematics, computer science, and biomedical technologies, Dr. Barati bridges engineering and medicine while enhancing his expertise through specialized training in programming, data analysis, and AI-driven healthcare applications. His research focuses on applying AI and computational simulations in radiotherapy and medical imaging, emphasizing brain tumor detection, classification, and radiation treatment modeling, while also extending to biomedical signal processing and machine learning applications for improved diagnostic accuracy and treatment planning. As a faculty member, he contributes to teaching, mentoring, research supervision, and interdisciplinary collaborations, publishing impactful work in Scopus-indexed journals. Recognized for his ability to mentor young researchers and his vision to advance precision medicine, Dr. Barati demonstrates leadership, innovation, and commitment to improving patient outcomes, making him a deserving candidate for the Best Researcher Award and an influential figure in the global scientific community.

Profile: Google Scholar | Scopus Profile | ORCID Profile

Featured Publications

  1. Noorimotlagh, Z., Mirzaee, S. A., Kalantar, M., Barati, B., Fard, M. E., & Fard, N. K. (2021). The SARS-CoV-2 (COVID-19) pandemic in hospital: An insight into environmental surfaces contamination, disinfectants’ efficiency, and estimation of plastic waste production. Environmental Research, 202, 111809.

  2. Mohseni, H., Amini, S., Abiri, B., Kalantar, M., Kaydani, M., Barati, B., Pirabbasi, E., & … (2021). Are history of dietary intake and food habits of patients with clinical symptoms of COVID-19 different from healthy controls? A case–control study. Clinical Nutrition ESPEN, 42, 280–285.

  3. Moghiseh, Z., Xiao, Y., Kalantar, M., Barati, B., & Ghahrchi, M. (2023). Role of bio-electrochemical technology for enzyme activity stimulation in high-consumption pharmaceuticals biodegradation. 3 Biotech, 13(5), 119.

  4. Barati, B., Erfaninejad, M., & Khanbabaei, H. (2025). Evaluation of effect of optimizers and loss functions on prediction accuracy of brain tumor type using a light neural network. Biomedical Signal Processing and Control, 103, 107409.

  5. Akbari, G., Mard, S. A., Savari, F., Barati, B., & Sameri, M. J. (2022). Characterization of diet based nonalcoholic fatty liver disease/nonalcoholic steatohepatitis in rodent models: Histological and biochemical outcomes. Universidad de Murcia, Departamento de Biología Celular e Histología.

Mr. Mohammad Hussein Amiri | Artificial Intelligence | Best Researcher Award

Mr. Mohammad Hussein Amiri | Artificial Intelligence | Best Researcher Award

Mohammad Hussein Amiri at Shahid Beheshti University, Iran

👨‍🎓 Profiles

Scopus

Orcid

An innovative data-driven AI approach for detecting and isolating faults in gas turbines at power plants

  • Authors: Mohammad Hussein Amiri, Nastaran Mehrabi Hashjin, Maryam Khanian Najafabadi, Amin Beheshti, Nima Khodadadi
    Journal: Expert Systems with Applications
    Year: 2025

Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm

  • Authors: Mohammad Hussein Amiri, Nastaran Mehrabi Hashjin, Montazeri, M., Mirjalili, S., Nima Khodadadi
    Journal: Scientific Reports
    Year: 2024

Monitoring UAV status and detecting insulator faults in transmission lines with a new classifier based on aggregation votes between neural networks by interval type-2 TSK fuzzy system

  • Authors: Mohammad Hussein Amiri, Mahdi Pourgholi, Nastaran Mehrabi Hashjin, Mohammadreza Kamali Ardakani
    Journal: Soft Computing
    Year: 2024

Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization

  • Authors: Nastaran Mehrabi Hashjin, Mohammad Hussein Amiri, Ardashir Mohammadzadeh, Seyedali Mirjalili, Nima Khodadadi
    Journal: Cluster Computing
    Year: 2024

Monitoring UAV Status and Detecting Insulation Defects in Transmission Lines with a New Hybrid Classifier based on the Type-2 Fuzzy and Neural Networks

  • Authors: Mohammad Hussein Amiri, Mahdi Pourgholi, Nastaran Mehrabi Hashjin, Mohammadreza Kamali Ardakani
    Journal: Research Square
    Year: 2023