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Nadia Skifa

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Nadia Skifa

G19a Cassie Building, Newcastle University, NE1 7RU

Biography

About Nadia

Previously holding a Rural Engineering degree from the Institute Hassan II of Agronomy and Veterinary Medicine (Morocco), I graduated with a Joint Master of Science (M. Sc.) degree in Hydroinformatics and Water Management from five universities (Polytech Nice Sophia, Brandenburgische Technische Universität, Newcastle University, and UPC Barcelona) as an Erasmus Mundus scholarship awardee. The focus of my studies was on the application of computational numerical models to all aspects of the water sector.

 

My academic journey is marked by a distinctive blend of advanced technical skills and a keen analytical mindset, honed through rigorous training and practical experiences across Africa, Europe, and Asia. My multilingual abilities in English, French, and Arabic have enabled me to collaborate effectively in diverse international settings, further enriching my expertise in Hydroinformatics.

 

During the last five years, I have undertaken various impactful internships at HydroSciences Montpellier and Incheon National University, where I leveraged machine learning and statistical techniques to tackle complex hydrological and water distribution challenges. These experiences gave me hands-on expertise in optimizing computational models and analyzing large datasets, underpinning my proficiency in programming languages such as Python, R, and MATLAB.

 

During my research internship at HydroSciences Montpellier, I explored the influence of dataset size and hydrometeorological typology on Long-Short Term Memory models for prediction accuracy, specifically for the Severn River (UK).

 

My MSc thesis was presented at the SimHydro Conference (2023) and will be printed in the Journal of Hydroinformatics 2024 and the Journal of Hydrology: (Impact of training dataset size and its hydrometeorological typology on LSTM performance for rainfall-runoff modeling: a case study of the Severn river – Archive ouverte HAL), and Comparison of an artificial neural network with a conceptual rainfall-runoff model for streamflow prediction – Archive ouverte HAL.

Research

MRes Research

For my MRes in Geospatial Systems at Newcastle University, I have been delving into advanced geospatial models and reliable tools such as big data and statistical data science. My PhD is a collaboration with WTWCo., focusing on modeling tailings dams. My commitment to excellence and proactive approach to problem-solving make me poised to contribute significantly to the field’s evolving landscape.

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