Mohammed Allawi | Engineering | Best Researcher Award

Dr. Mohammed Allawi | Engineering | Best Researcher Award

University of Anbar,  Iraq

Mohammed Falah Allawi, an Iraqi national, is a distinguished civil engineer specializing in water surface hydrology, dams engineering, and fluid mechanics. He holds a PhD in Civil Engineering from the National University of Malaysia and serves as a lecturer at the University of Anbar.

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📚 Education:

Mohammed earned his B.Sc. in Dams and Water Resources Engineering from the University of Anbar in 2010, followed by an M.Sc. and a PhD in Civil Engineering from the National University of Malaysia in 2016 and 2019, respectively.

🏢 Experience:

He has extensive experience as a field engineer in various construction projects and has lectured at Al Maarif University College and the University of Anbar.

🔍 Research Interests:

His research interests span water resources planning, steel structures, advanced soil mechanics, and the application of artificial intelligence in hydro-environmental modeling.

🏆 Awards:

Mohammed has been recognized for his contributions in environmental ergonomics and holds memberships in several engineering associations across Iraq and the Arab region.

📝 Publications:

Neurocomputing, 2022 – Groundwater level prediction using machine learning models: A comprehensive review. Cited by 186.

Neural Computing and Applications, 2018 – Non-tuned machine learning approach for hydrological time series forecasting. Cited by 101.

Neural Computing and Applications, 2019 – A hybrid bat–swarm algorithm for optimizing dam and reservoir operation. Cited by 97.

Scientific Reports, 2020 – Input attributes optimization using the feasibility of genetic nature inspired algorithm: application of river flow forecasting. Cited by 73.

Environmental Science and Pollution Research, 2018 – Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models. Cited by 66.

RBFNN-based model for heavy metal prediction for different climatic and pollution conditions