Assist. Prof. Dr. Nevra Karamüftüoğlu | Artificial Neural Networks | Research Excellence Award

Assist. Prof. Dr. Nevra Karamüftüoğlu | Artificial Neural Networks | Research Excellence Award

Assistant Professor | Gülhane Faculty of Dentistry, University of Health Sciences | Turkey

Assist. Prof. Dr. Nevra Karamüftüoğlu is an accomplished academic and researcher whose work integrates pediatric dentistry with advanced Artificial Neural Networks to address contemporary clinical and societal challenges. Her expertise centers on Artificial Neural Networks driven decision support systems, diagnostic modeling, and data interpretation in dental sciences, where Artificial Neural Networks are applied to radiographic analysis, preventive strategies, and patient education. Through interdisciplinary collaborations, Artificial Neural Networks have been utilized to enhance biomaterials research, sustainability practices, and intelligent clinical workflows. Her scholarly output includes peer reviewed publications where Artificial Neural Networks support evidence based methodologies, improve accuracy, and strengthen reproducibility. Artificial Neural Networks also underpin her collaborative research with clinicians and engineers, enabling translational impact from laboratory innovation to patient care. The societal relevance of her work is reflected in the use of Artificial Neural Networks to promote preventive oral health, digital literacy, and equitable healthcare delivery. Overall, Artificial Neural Networks represent a unifying framework across her research, teaching, and service, reinforcing global relevance and scientific rigor. Scopus profile of 26 Citations, 7 Documents, 2 h- index.

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Featured Publications

Dr. Yu Peng | Artificial Neural Networks | Best Researcher Award

Dr. Yu Peng | Artificial Neural Networks | Best Researcher Award

Associate Research Fellow | East China University of Science and Technology | China

Dr. Yu Peng, Associate Research Fellow at the School of Materials Science and Engineering, East China University of Science and Technology, has built an impressive academic and research career with a strong focus on materials chemistry and energy-related applications, where Artificial Neural Networks play a pivotal role in his innovative work. With a B.Sc. in Pharmacy from Nanchang University and a Ph.D. in Physical Chemistry under joint supervision at ShanghaiTech University and the Chinese Academy of Sciences, he deepened his expertise before advancing as a Post-doctor and then securing his current academic position. Dr. Yu Peng’s professional experience demonstrates his dedication to exploring polar and ferroelectric materials, two-dimensional photoelectric materials, photocatalytic hydrogen production, and photocatalytic biomass conversion, where Artificial Neural Networks are consistently applied to enhance predictive modeling, structural optimization, and performance analysis. His research has earned prestigious awards such as the Carbon Future Young Investigator Honorable Mention Award and multiple national scholarships, reflecting his outstanding contributions to science. Widely published in leading journals, his work bridges experimental material synthesis with Artificial Neural Networks modeling to design high-performance perovskites and hybrid semiconductors. His research skills encompass advanced materials characterization, computational simulations, and integration of Artificial Neural Networks in analyzing photoelectric and catalytic behaviors. Dr. Yu Peng’s career reflects a fusion of theoretical insight and practical applications, and his achievements in Artificial Neural Networks demonstrate his commitment to driving forward sustainable energy materials, innovative photocatalysts, and advanced optoelectronic devices, making him a recognized contributor to the global research community.

Profile: ORCID

Featured Publications

1. Zhang, J., Zhang, Y., Peng, Y., Wang, M. M., Zhu, Y., Wang, X., Tang, Y. Y., Ding, P. C., Liu, P. F., & Yang, H. G. (2025). Template-free synthesis of single-crystal SrTiO₃ nanocages for photocatalytic overall water splitting. Chemical Communications.

2. Peng, Y., Li, L., Xu, Y., Wang, X., & Hou, Y. (2025). Two-dimensional multilayered ferroelectric with polarization-boosted photocatalytic hydrogen evolution. Catalysts.

3. Peng, Y., Zhang, Y., Wang, X., Sui, X. Y., Lin, M. Y., Zhu, Y., Jing, C., Yuan, H. Y., Yang, S., Liu, P. F., et al. (2024). Polar aromatic two-dimensional Dion–Jacobson halide perovskites for efficient photocatalytic H₂ evolution. Angewandte Chemie.

4. Peng, Y., Zhang, Y., Wang, X., Sui, X. Y., Lin, M. Y., Zhu, Y., Jing, C., Yuan, H. Y., Yang, S., Liu, P. F., et al. (2024). Polar aromatic two-dimensional Dion–Jacobson halide perovskites for efficient photocatalytic H₂ evolution. Angewandte Chemie International Edition.

5. Liu, D., Zheng, Y., Sui, X. Y., Wu, X. F., Zou, C., Peng, Y., Liu, X., Lin, M., Wei, Z., Zhou, H., et al. (2024). Universal growth of perovskite thin monocrystals from high solute flux for sensitive self-driven X-ray detection. Nature Communications.