Assoc. Prof. Dr. Ipek Atik | Health | Research Excellence Award

Assoc. Prof. Dr. Ipek Atik | Health | Gaziantep Islam Science and Technology University | Turkey

Health plays a central role in the scientific contributions of Assoc. Prof. Dr. Ipek Atik, whose career spans advanced research in deep learning, machine learning, renewable energy forecasting, medical image analysis, and computational modeling. Assoc. Prof. Dr. Ipek Atik has built a strong academic foundation through her formal education, progressing from engineering studies into specialized research areas involving artificial intelligence applications to health systems, environmental sustainability, and complex data-driven prediction models. Her professional experience includes serving as an academic and researcher at Gaziantep Islam Science and Technology University, where she has contributed extensively to AI-driven classification systems, forecasting methodologies, radiation shielding research, and medical imaging solutions, particularly in pneumonia detection and COVID-19 case prediction—fields where health, technology, and engineering effectively converge. Throughout her career, Assoc. Prof. Dr. Ipek Atik has cultivated broad research interests spanning convolutional neural networks, short-term energy forecasting, satellite image classification, landform analysis, LED technologies, renewable energy systems, and advanced material characterization, demonstrating an interdisciplinary approach that strengthens the health and engineering research ecosystem. Her demonstrated research skills include algorithm development, regression learning, deep learning model optimization, transfer learning, optical systems analysis, neural network-based forecasting, materials computation, and the integration of AI with medical and environmental datasets. These skills are strongly supported by her impactful publication record, which has earned awards and honors through high citation counts, international collaborations, and recognition within journals focused on engineering, energy, radiation sciences, and computational technologies. With over 220 citations, an h-index of 8, and an i10-index of 6, Assoc. Prof. Dr. Ipek Atik has established a meaningful global research presence. Her work on CNN-based classification systems, drone detection enhancement, short-term energy load forecasting, and deep learning–supported medical analysis highlights the significant influence of her studies on public health, technological advancement, and industrial applications. The sustained academic output of Assoc. Prof. Dr. Ipek Atik, combined with her dedication to interdisciplinary innovation, positions her as a leading contributor to modern AI-enabled solutions. In conclusion, Assoc. Prof. Dr. Ipek Atik represents a dynamic and forward-focused researcher whose work consistently bridges health, engineering, and artificial intelligence, contributing valuable insights and technologies that support societal progress, scientific advancement, and long-term sustainable development.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

Atik, I. (2022). Classification of electronic components based on convolutional neural network architecture. 39 citations.
Atik, I. (2022). A new CNN-based method for short-term forecasting of electrical energy consumption in the COVID-19 period: The case of Turkey. 32 citations.
Dinçer, F., Atik, İ., Yılmaz, Ş., & Çıngı, A. (2017). Hidrolik enerjisinden yararlanmada ülkemiz ve gelişmiş ülkelerin mevcut durumlarının analizi. 26 citations.
Atik, I. (2023). CB-YOLOv5: Enhancing drone detection with BottleneckCSP and cross convolution for improved performance. 16 citations.
Tuncel, N., Akkurt, I., Atik, I., Malidarre, R. B., & Sayyed, M. I. (2024). Neutron-gamma shielding properties of chalcogenide glasses. 11 citations.
Atik, I. (2022). Performance comparison of regression learning methods: COVID-19 case prediction for Turkey. 10 citations.