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Personal profile


Majdi Fanous is a postgraduate researcher at the Centre of Computational Science and Mathematical Modelling (CSM) at Coventry University. He is conducting his research under the Global Challenges Research Fund (GCRF).

In addition to his research, Majdi has assisted in delivering several modules at Coventry University including statistics, machine learning, and artificial neural networks. He has also co-supervised multiple postgraduate students in their Masters project.

After receiving a Bachelor of Engineering degree in Chemical Engineering from the American University of Beirut (AUB), Lebanon, he went on to pursue a Master of Science degree in Data Science and Computational Intelligence at Coventry University.

Research Interests

Majdi's research interests are in developing fast, efficient, and accurate machine learning surrogate models to replace complex numerical models. The application of his research is in modelling the hydro-morphodynamics of mangrove environments to quantify their ability to mitigate climate change impacts such as sea-level rise and coastal erosion.

PhD Project

Enhancing Mangrove Forest Resilience Against Coastal Degradation and Climate Change Impacts Using Advanced Bayesian Machine Learning Methods

Supervisory Team

Dr Alireza Daneshkhah (Director of Study)

Dr Jonathan Eden

Dr Vasile Palade

Dr Renji Remesan (External - IIT)

Master's Project

Modelling of Hydro-Morphodynamic Systems Using Deep Gaussian Process

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 1 - No Poverty
  • SDG 6 - Clean Water and Sanitation
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 13 - Climate Action
  • SDG 15 - Life on Land

Education/Academic qualification

Data Science and Computational Intelligence, MSc, Modelling of Hydro-Morphodynamic Systems Using Deep Gaussian Process, Coventry University

17 Jan 202014 Jan 2021

Award Date: 14 Jan 2021

Chemical Engineering, Degree, American University of Beirut

1 Sept 20151 May 2019

Award Date: 1 May 2019


  • QA76 Computer software
  • Gaussian Processes


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