Ipek Atik | Health | Research Excellence Award

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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.

 

 

Yunju Xiao | Biosensors | Best Researcher Award

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Mrs. Yunju Xiao | Biosensors | Best Researcher Award

Mrs. Yunju Xiao | Biosensors | Junior Physician at Guangdong Provincial People’s Hospital | China

Mrs. Yunju Xiao is an accomplished researcher specializing in biomedical sensing, nanomaterials-based analytical systems, and molecular diagnostics, recognized for her contributions to advancing innovative detection platforms for clinical and translational applications. She completed her education through rigorous training in medical sciences and research methodology, culminating in a doctoral qualification from a leading medical university where she focused on the development of nano-enabled biosensing technologies for sensitive biomarker identification and disease monitoring. Building on her academic foundation, she has gained significant professional experience at Guangdong Provincial People’s Hospital of Southern Medical University, where she contributes to multidisciplinary projects aimed at improving diagnostic precision and healthcare outcomes. Her research interests span catalytic hairpin assembly mechanisms, gold nanoparticle engineering, signal-enhanced detection systems, surface-enhanced Raman spectroscopy, and microRNA-based disease diagnostics, reflecting her dedication to bridging basic nanoscience with practical clinical applications. Mrs. Yunju Xiao’s research skills include expertise in nanoscale material synthesis, molecular probe design, advanced spectroscopic techniques, microfluidic diagnostics, data interpretation, and laboratory protocol optimization, allowing her to make meaningful contributions to emerging diagnostic research. She has authored multiple peer-reviewed publications indexed in Scopus and other leading databases, accumulating notable citations that reflect the visibility and academic value of her work. Her recognized publication in Sensors and Actuators B: Chemical demonstrates her ability to produce impactful research within competitive scientific fields. Throughout her academic and professional career, she has earned recognition for her scholarly output and has received honors for her contribution to collaborative research efforts and high-quality scientific dissemination. Her involvement in scientific communities further supports her commitment to continuous learning and professional advancement. Mrs. Yunju Xiao’s work reflects analytical rigor, innovation, and a strong commitment to addressing scientific challenges related to early disease detection and diagnostic sensitivity. She continues to expand her research through interdisciplinary collaborations, aiming to contribute to the development of next-generation biosensing systems. In conclusion, Mrs. Yunju Xiao exemplifies a promising and dedicated researcher whose background in biomedical diagnostics, strong methodological skills, and expanding publication record position her as an influential contributor to the future of diagnostic technology and biomedical research.

Academic Profile: ORCID | Scopus

Featured Publications:

  1. Xiao, Y. (2026). Catalytic hairpin assembly (CHA)-driven AuNP tetramer assembly-based SERS platform for sensitive detection of EV-miRNAs. Sensors and Actuators B: Chemical.