Assoc. Prof. Dr. Mohamed El-Metwally | Environmental Analytical Chemistry | Best Researcher Award

Assoc. Prof. Dr. Mohamed El-Metwally | Environmental Analytical Chemistry | Best Researcher Award

Assoc. Prof. Dr. Mohamed El-Metwally | National Institute of Oceanography and Fisheries | Egypt

Assoc. Prof. Dr. Mohamed El-Metwally is an accomplished researcher in marine environmental science with strong expertise in pollution studies, water treatment, biodiversity, and ecological assessment. He holds a BSc and PhD in Science from Mansoura University and an MSc from Alexandria University, complemented by advanced international training through the GAME program at IFM-Geomar in Germany, a UNESCO-IHE course in the Netherlands, a research fellowship at the University of Pavia in Italy, and a postdoctoral research grant at the Georgia Institute of Technology in the USA. Since 2008, he has contributed significantly to the National Institute of Oceanography and Fisheries, where he has developed extensive experience in environmental monitoring, emergent contaminants, aquatic ecosystem health, and advanced laboratory techniques. His work bridges applied research and environmental protection, focusing on improving water quality, understanding pollution pathways, and promoting sustainable marine resource management. Throughout his career, he has been recognized through competitive fellowships and international research opportunities that highlight his scientific impact. With a commitment to advancing marine environmental science, Dr. El-Metwally continues to contribute knowledge that supports conservation efforts, ecological sustainability, and innovative solutions to modern environmental challenges.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Sallam, A., El-Metwally, M., Sabry, M.A., & Elsbaey, M. (2021). Cladamide: a new ceramide from the endophytic fungus Cladosporium cladosporioides. Natural Product Research.

El-Metwally, M.E.A., Darwish, D.H., & Dar, M.A. (2021). Spatial distribution and contamination assessment of heavy metals in surface sediments of Lake Burullus, Egypt. Arabian Journal of Geosciences.

El-Sayed, W.M.M., Elshaer, M.M., Ibrahim, H.A.H., & El-Metwally, M.E.A. (2020). Antimicrobial agents from sea urchin (Diadema setosum) collected from the Red Sea, Egypt. Egyptian Journal of Aquatic Biology and Fisheries.

El-Metwally, M.E.A., Othman, A.I., & El-Moselhy, K.M. (2019). Distribution and assessment of heavy metals in the coastal area of the Red Sea, Egypt. Egyptian Journal of Aquatic Biology and Fisheries.

Elsbaey, M., Sallam, A., El-Metwally, M., Nagata, M., Tanaka, C., Shimizu, K., & Miyamoto, T. (2019). Melanogenesis inhibitors from the endophytic fungus Aspergillus amstelodami. Chemistry & Biodiversity.

Al Prol, A.E., El-Metwally, M.E.A., & Amer, A. (2019). Sargassum latifolium as eco-friendly materials for treatment of toxic nickel (II) and lead (II) ions from aqueous solution. Egyptian Journal of Aquatic Biology and Fisheries.

Mahmoud, M.A.M., Dar, M.A., Hussein, H.N.M., El-Metwally, M.E.A., Maaty, M.M., Omar, M.Y., Seraj, M.R., & Mohammed, T.A.A. (2019). Survivorship and growth rates for some transplanted coral reef-building species and their potential for coral reef rehabilitation in the Red Sea. Egyptian Journal of Aquatic Biology and Fisheries.

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

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