Yuan Xue | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Assoc Prof. Dr. Yuan Xue | Statistical Applications in Engineering | Best Researcher Award

Chengdu University of Technology | China

Assoc Prof. Dr. Yuan Xue, an accomplished Associate Professor at Chengdu University of Technology, is a leading researcher in the specialized domain of earthquake statistics and geostatistical modeling, with a strong record of academic excellence, scientific innovation, and professional service. His research career is distinguished by substantial contributions to statistical inference in seismicity, the development of earthquake probability models, and the quantitative assessment of seismic hazard patterns across major fault systems in Sichuan, China. Over the years, he has independently led two provincial-level scientific research projects and participated as a principal contributor in two major national-level initiatives, including one supported by the National Key Research and Development Program and another funded by the National Natural Science Foundation of China. In addition, he has been involved in eight provincial-level scientific projects and has successfully completed a total of fifteen scientific and consultancy projects in both academic and applied settings. Dr. Xue has demonstrated prolific scholarly output, publishing seventeen peer-reviewed journal articles as first or corresponding author across SCI, Scopus, and other prestigious platforms, contributing significantly to advancements in earthquake statistical theory and practical seismic risk analysis. His Scopus academic profile further reflects his growing global impact, with an h-index of 26, 8 documents, and 174 citations, complementing his broader citation record of 18 citations in Web of Science and 88 citations in CNKI. He has also contributed to academic literature through the publication of three books with internationally recognized ISBNs and has secured four national invention patents, demonstrating the applied value and innovation of his work. Dr. Xue’s expertise extends to professional academic service, serving as a reviewer and editor of the South China Journal of Seismology, as well as collaborating with the Sichuan Earthquake Agency to carry out high-impact statistical inference studies on seismic patterns of major regional fault systems. His research achievements have been recognized through multiple awards, including two second prizes in National Land and Resources Science and Technology, a second prize in Sichuan Province Science and Technology Progress, and a prestigious first prize in the Sichuan Province On-site Statistics Society Excellent Achievement Award. As an active member of the Chinese Association for Applied Statistics, the Chinese Mathematical Society, and the Sichuan Association for Applied Statistics-where he also serves as Deputy Secretary-General, Dr. Xue continues to expand the role of statistical science in earthquake research, contributing meaningful advancements to national and regional seismic safety and hazard prediction efforts.

Profile: Scopus 

Featured Publications

Wei, D., Xue, Y., Wang, X., Liu, W., & He, J. (2025). Stability monitoring of deep soil in slope based on local strain and continuous vibration information analysis. Optical Fiber Technology,

Li, T., Tian, J., Pei, X., Guo, J., Chen, M., Xue, Y., & Meng, M. (2025). Shear strength indices predication model for coarse-grained soil based on particle gradation and moisture content information. Bulletin of Engineering Geology and the Environment,

Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

Published on by Statistics

Dr. Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

C.V. Raman Global University | India

Dr. Abhijeet Das, Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, is an accomplished civil engineering researcher specializing in watershed hydrology, hydrological modeling, climate change impact assessment, and GIS-based water resources management. With a strong academic foundation, including M.Tech and B.Tech degrees from Biju Patnaik University of Technology, he has combined rigorous research with nearly a decade of professional and teaching experience. Dr. Das has contributed extensively to collaborative national and international projects across Tunisia, USA, Oman, UK, South Africa, Syria, and Lebanon, focusing on water quality, hydrologic extremes, and sustainable water management through remote sensing, machine learning, and optimization techniques. He has published 88 documents indexed in Scopus, which have received 199 citations, achieving an h-index of 7, reflecting both productivity and the growing impact of his research contributions. His intellectual property portfolio includes over 30 patents filed in water resource engineering, geoinformatics, and environmental sustainability, showcasing innovation and applied problem-solving capacity. Dr. Das has actively engaged in more than 30 seminars, workshops, and international conferences, presenting advancements in civil and water resource engineering. His career trajectory illustrates a blend of academic excellence, applied research, and industry collaboration, making him a promising contributor to the advancement of sustainable infrastructure and water management systems.

Profiles: Scopus | Orcid

Featured Publications

Das, A. (2025). An optimization-based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment.

Das, A., & Mishra, S. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Discover Sustainability.

Das, A. (2025). A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India. Discover Sustainability.

Das, A. (2025). Evaluation and prediction of surface water quality status for drinking purposes using integrated water quality indices, GIS approaches, and machine learning techniques. Desalination and Water Treatment.

Das, A., Mishra, S., & Tripathy, B. (2025). Bioplastics: A sustainable alternative or a hidden microplastic threat? Innovative Infrastructure Solutions.