Stela Jokić | Engineering | Best Researcher Award

Prof Dr. Stela Jokić | Engineering | Best Researcher Award

Vice-Dean, Faculty of Food Technology Osijek, Croatia

Stela Jokić is a distinguished Associate Professor at the Faculty of Food Technology Osijek, Croatia. With over a decade of experience in academia, she specializes in food technology and process optimization. Her research is noted for its impact on supercritical fluid extraction and medicinal plant extracts, contributing significantly to the fields of food safety and industrial process design. 🌟

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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