Yuyao Wang | Artificial Intelligence | Best Scholar Award

Mr. Yuyao Wang | Artificial Intelligence | Best Scholar Award

Master's Candidate | Henan Polytechnic University | China

Mr. Yuyao Wang, a Master’s candidate in Cartography and Geographic Information Systems at Henan Polytechnic University, has made significant contributions to remote sensing and artificial intelligence integration for agricultural and environmental monitoring. His research primarily focuses on remote sensing image processing, land use classification, and artificial intelligence-driven multi-source data fusion. With strong expertise in applying artificial intelligence to satellite data interpretation, Mr. Wang has developed novel frameworks for rice field identification in mountainous regions and cloud removal techniques using SAR and optical imagery fusion. His innovative use of artificial intelligence in remote sensing enhances precision agriculture and sustainable land management practices. Mr. Wang’s professional journey reflects his commitment to applying artificial intelligence and geospatial analytics to complex real-world challenges. His works published in prestigious journals like Remote Sensing and PLOS ONE demonstrate robust analytical skills, methodological innovation, and interdisciplinary thinking powered by artificial intelligence. He continues to explore advanced artificial intelligence techniques for improving data accuracy and environmental insights, bridging gaps between technology and agricultural sciences. Mr. Wang’s achievements highlight excellence in artificial intelligence research, demonstrating potential for transformative advancements in geoinformatics and environmental sustainability. His dedication, scientific curiosity, and mastery of artificial intelligence tools reinforce his reputation as a promising researcher in remote sensing and GIS. 12 Citations, 3 Documents, 2 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Wang, Y., Cheng, J., Yuan, Z., & Zang, W. (2025). Research on rice field identification methods in mountainous regions. Remote Sensing, 17(19), 3356.

2. Wang, Y. (2025, March 19). A novel cloud removal method by fusing features from SAR and neighboring optical remote sensing images.

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.