Dr. Abhijeet Das | Civil Infrastructure | Water Treatment Award

Dr. Abhijeet Das | C.V. Raman Global University | India

Dr. Abhijeet Das is a distinguished researcher in water resources and Geographic Information Systems (GIS), recognized for his extensive contributions to spatial analysis, hydrological modeling, and environmental assessment. His research emphasizes evaluating water vulnerability, hydro-environmental risks, and watershed dynamics through the integration of remote sensing data, GIS-based multi-criteria analysis, and climate impact modeling. With 94 documents, 265 citations from 139 sources, and an h-index of 9 in Scopus, his scholarly work demonstrates significant impact in the fields of hydrology, geospatial science, and environmental sustainability. Dr. Das’s professional expertise spans remote sensing for water quality monitoring, GIS-based Water Quality Index mapping, and advanced hydrological simulations using tools such as SWAT, HEC-HMS, and MIKE SHE. His technical proficiency includes ArcGIS, QGIS, Python, MATLAB, and Google Earth Engine, complemented by applications of IoT-based sensor systems for real-time water quality assessment. As a peer reviewer with 62 reviews for 25 publications and grants recorded in ORCID, he plays an active role in maintaining research quality within the scientific community. Dr. Das’s work continues to advance sustainable water resource management, climate resilience, and data-driven environmental decision-making across regional and interdisciplinary contexts.

Profiles: Scopus | Orcid

Featured Publications

Das, A. (2025). Drinking water resources suitability assessment in Brahmani River, Odisha based on pollution index of surface water utilizing advanced water quality methods. Scientific Reports.

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, 2 citations.

Das, A. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Review Article, 2 citations.

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, 3 citations.

Das, A. (2025). Surface water quality evaluation impacting drinking water sources and sanitation using water quality index, multivariate techniques, and interpretable machine learning models in Mahanadi River, Odisha (India). Review Article.

Das, A. (2025). Water quality assessment and geospatial techniques for the delineation of surface water potential zones: A data-driven approach using machine learning models. Desalination and Water Treatment.

Dr. Bin Zhang | Structural Engineering | Best Researcher Award

Dr. Bin Zhang | Chongqing University of Science and Technology | China

Dr. Bin Zhang holds a Doctorate in Engineering and has completed postdoctoral research. He is a lecturer and master’s supervisor in the Department of Road and Bridge Engineering, School of Civil and Hydraulic Engineering, and a youth committee member of the World Transport Convention. His research focuses on the dynamic characteristics of underground and tunnel structures, the development of new materials and technologies for structural reinforcement, and intelligent monitoring of structural health. His research output includes 26 documents, 171 citations, 146 citing documents, and an h-index of 8. He teaches both undergraduate and postgraduate courses, including Tunnel Engineering, Engineering Surveying, Tunnel Mechanics, and Frontier Technologies in Civil Engineering, integrating theoretical knowledge with practical applications to advance innovation in civil and tunnel engineering. Additionally, he has developed advanced experimental methods for studying tunnel lining mechanics, contributing to safer and more efficient tunnel design practices.

Profile: Scopus | Orcid

Featured Publications

Study on the Stability of Buildings During Excavation in Urban Core Areas, Applied Sciences, 2025. Contributors: Kang Liu, Huafeng Liu, Yuntai Gao, Zijian Wang, Yunchuan Wang, Qi Liu, Chaolin Jia, Zihang Huang, Bin Zhang.
Experimental Study on Mechanical Differences Between Prefabricated and Cast-In Situ Tunnel Linings Based on a Load-Structure Model, Buildings, 2025. Contributors: Li-Ming Wu, Hong-Kun Li, Feng Gao, Zi-Jian Wang, Bin Zhang, Wen-Jie Luo, Jun-Jie Li.
Mechanical Properties of Steel Fiber-Reinforced Concrete Tunnel Secondary Lining Structure and Optimization of Support Parameters, Buildings, 2025. Contributors: Zijian Wang, Yunchuan Wang, Xiaorong Wang, Baosheng Rong, Bin Zhang, Liming Wu, Chaolin Jia, Zihang Huang.
Crystallization Blockage in Highway Tunnel Drainage System Based on Molecular Dynamics, AIP Advances, 2025. Contributors: Shiyang Liu, Xuefu Zhang, Bin Zhang.
Experimental Study on Grouting Diffusion Law of Tunnel Secondary Lining Cracks Based on Different Slurry Viscosities, Applied Sciences, 2025. Contributors: Bin Zhang, Peng Liu, Yi Wu, Liming Wu, Chen Li, Shiyang Liu, Yuanfu Zhou.
Experimental Study on Grouting Diffusion Law of the Different Crack Widths in Tunnel Lining, KSCE Journal of Civil Engineering, 2023. Contributors: Bin Zhang, Yuanfu Zhou, Xuefu Zhang, Zijian Wang, Wei Yang, Yixuan Ban.
Anti Crystallization Blocking of Flocking Drainage Pipe Based on Natural Phenomenon, Materials Science, 2022. Contributors: Xuefu Zhang, Shiyang Liu, Feng Gao, Yuanfu Zhou, Bin Zhang.