PHD at University Putra Malaysia, Malaysia
Dr. Saad Shauket Sammen, an Assistant Professor at the Department of Civil Engineering, University Putra Malaysia, specializes in water resources engineering. Born in Diyala, Iraq, in 1978, he holds a Ph.D. from University Putra Malaysia and a Master’s from the University of Technology, Iraq. His research interests include water resources management, hydraulic and hydrology modeling, groundwater modeling, and climate change. Dr. Sammen has extensive teaching experience and has supervised several postgraduate students. He has also served as a consultant on numerous hydrological and construction projects in Iraq and Malaysia, contributing significantly to the field of water resources engineering. Machine Learning
Professional Profiles
Education
Ph.D. in Water Resources Engineering Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Malaysia (2017) Master of Water Resources Engineering Department of Building and Construction, University of Technology, Iraq (2009) Bachelor of Civil Engineering Department of Civil Engineering, College of Engineering, University of Anbar, Iraq (2001) Machine Learning
Work Experience
Assistant Professor Department of Civil Engineering, University Putra Malaysia (2021-present) Lecturer Civil Engineering Department, University of Diyala (2017-2021) Ph.D. Student Department of Civil Engineering, University Putra Malaysia (2014-2017) Lecturer Civil Engineering Department, University of Diyala (2011-2013) Assistant Lecturer Civil Engineering Department, University of Diyala (2009-2011) Civil Engineer Ministry of Higher Education and Scientific Research, Iraq (2006-2009) Civil Engineer Ministry of Water Resources, Iraq (2004-2006)
Teaching Experience
Lecturer Civil Engineering Department, University of Diyala, teaching: Fluid Mechanics for 2nd-year undergraduates Mathematics for 2nd-year undergraduates Hydraulic Structures for 3rd-year undergraduates Irrigation and Drainage Engineering for 4th-year undergraduates Machine Learning
Research Area Interest
Water Resources Management Hydraulic Modeling Hydrology Modeling Ground Water Modeling Climate Change Water Quality Modeling GIS and RS in Water Resources Application of Artificial Intelligence and Optimization Algorithms in Water Resources Engineering
Research Focus
Dr. Saad Shauket Sammen is an expert in water resources engineering, focusing on rainfall-runoff modeling, water quality assessment, and drought prediction using advanced machine learning techniques. His research, widely published in high-impact journals, explores the application of evolutionary algorithms like Harris Hawks Optimizer and Particle Swarm Optimization for hydrological modeling. Dr. Sammen has made significant contributions to understanding and predicting water-related phenomena, utilizing hybrid machine learning models to improve the accuracy and efficiency of environmental and hydrological predictions. His work is instrumental in developing sustainable water management practices, particularly in the face of climate change and increasing water scarcity. Machine Learning
Publications
- Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India, Publication date: 2024.
- Predictive modelling of nitrogen dioxide using soft computing techniques in the Agra, Uttar Pradesh, India, Publication date: 2024.
- Toward Decontamination in Coastal Regions: Groundwater Quality, Fluoride, Nitrate, and Human Health Risk Assessments within Multi-Aquifer Al-Hassa, Saudi Arabia, Publication date: 2024.
- Developing an ensembled machine learning model for predicting water quality index in Johor River Basin, Publication date: 2024.
- Isotherms, kinetics and thermodynamic mechanism of methylene blue dye adsorption on synthesized activated carbon, Publication date: 2024.
- Three novel cost-sensitive machine learning models for urban growth modelling, Publication date: 2024.
- Strength assessment of structural masonry walls: analysis based on machine learning approaches, Publication date: 2024.
- Prediction of daily leaf wetness duration using multi-step machine learning, Publication date: 2024.
- New strategy based on Hammerstein–Wiener and supervised machine learning for identification of treated wastewater salinization in Al-Hassa region, Saudi Arabia, Publication date: 2024.
- Comparison Analysis of Seepage Through Homogenous Embankment Dams Using Physical, Mathematical and Numerical Models, Publication date: 2024.
.