Jinjian Ding | Emerging Contaminants |Research Excellence Award

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Assoc. Prof. Dr. Jinjian Ding | Emerging Contaminants | Research Excellence Award

Zhejiang Shuren University | China

Assoc. Prof. Dr. Jinjian Ding is an Associate Researcher at the Institute of Interdisciplinary Sciences, Zhejiang Shuren University, with a strong academic background in environmental science and interdisciplinary research. He earned his Ph.D. in Environmental Science from Zhejiang University (2011–2016) after completing his B.Sc. in Environmental Science at Zhejiang University of Technology (2007–2011). Following his doctoral studies, he carried out postdoctoral research at the Taizhou Institute of Zhejiang University (2016–2019), where he was actively involved in energy and environmental engineering research. His professional career includes roles as Assistant Researcher at the Taizhou Institute of Zhejiang University, Lecturer at the College of Quality and Safety Engineering, China Jiliang University, and Associate Researcher at the same institution before joining Zhejiang Shuren University in 2023. His research interests broadly focus on environmental science, energy and environmental engineering, quality and safety engineering, pollution control, and interdisciplinary environmental applications. Dr. Ding has contributed to multiple research projects, published scholarly works, and participated in academic collaborations, earning recognition through research grants and institutional awards. Through his teaching, research, and interdisciplinary engagement, he continues to advance sustainable environmental solutions and contribute meaningfully to higher education and scientific innovation.

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Featured Publications

Noel Isack Kaaya | Geochemistry | Research Excellence Award

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Mr. Noel Isack Kaaya | Geochemistry | Research Excellence Award

Government Chemist Laboratory Authority, Tanzania

Mr. Noel Isack Kaaya is an accomplished chemist and researcher with extensive expertise in hazardous chemical management, environmental monitoring, and analytical toxicology. He holds a Master of Science in Chemistry from the University of Dodoma and a Bachelor of Science in Chemistry from the University of Dar es Salaam, which laid the foundation for his strong scientific and analytical capabilities. With over a decade of professional experience at the Government Chemist Laboratory Authority, he has played a key role in conducting laboratory analyses related to environmental pollution, occupational safety, health risk assessment, and the detection of illicit substances. His research interests span acid mine drainage, soil contamination, geogenic pollutants, carcinogenic risk assessment, and the application of advanced analytical techniques to address environmental and public health challenges. He has contributed to peer-reviewed publications and has been recognized for his commitment to scientific integrity and service to environmental protection. Driven by a passion for improving chemical safety and promoting evidence-based environmental management, he continues to advance his expertise through research, collaboration, and capacity building. His career reflects dedication, professionalism, and a strong commitment to safeguarding communities through scientific excellence.

Profiles: Scopus | Orcid

Featured Publications

Kaaya, N.I., Vegi, M.R., & Macheyeki, A.S. (2026). “Acid mine drainage, soil pollution, and carcinogenic risk of geogenic contaminants in artisanal and small-scale gold mining areas of Geita, Tanzania.” Environmental Geochemistry and Health. https://doi.org/10.1007/s10653-025-02909-8

Kaaya, N.I., Vegi, M.R., & Macheyeki, A.S. (2025). “Graphene-based adsorbents for selective recovery of rare earth elements from mining wastes: A review.” FlatChem. https://doi.org/10.1016/j.flatc.2025.100954

Kaaya, N.I., Vegi, M.R., & Macheyeki, A.S. (2025). “Health risks of geogenic contaminants in gold mining areas in Geita, Tanzania.” Journal of Trace Elements and Minerals. https://doi.org/10.1016/j.jtemin.2025.100222

Dr. Abhijeet Das | Water Resource Engineering | Distinguished Scientist Award

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Dr. Abhijeet Das | Water Resource Engineering | Distinguished Scientist Award

C.V. Raman Global University (CGU), Bhubaneswar | India

Dr. Abhijeet Das is an accomplished water resource engineer specializing in watershed hydrology, hydrological modeling, water quality control, and climate change impact assessment. He holds a B.Tech in Civil Engineering from ABIT College (BPUT, Rourkela), an M.Tech in Water Resource Engineering from the College of Engineering and Technology (BPUT, Bhubaneswar), and a Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar. With extensive experience in GIS, remote sensing, and geoinformatics, he has contributed significantly to hydrological modeling, flood and drought assessment, and the integration of machine learning techniques for water resource management. Dr. Das has held positions as a GIS Analyst, Teaching Assistant, and Research Consultant, leading spatial data management, hydrological and hydraulic modeling, flood risk analysis, and multi-criteria decision support. His expertise spans numerical modeling, optimization techniques, artificial neural networks, and fuzzy logic for environmental and water systems. He has successfully guided GIS projects, developed dashboards for real-time monitoring, and collaborated with government agencies for watershed and crop management planning. Dr. Das’s research focuses on sustainable water management, climate resilience, and the Food-Energy-Water (FEW) nexus. His contributions have advanced environmental impact assessment and decision-making tools. He continues to drive innovation in water resource engineering and hydrological research, fostering a data-driven approach to sustainable resource management.

Profile: Scopus

Featured Publications

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

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.

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.

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

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