Dr Nadhir Ben Rached

Profile

I received the Diplôme d’Ingénieur degree from École Polytechnique de Tunisie (EPT), La Marsa, Tunisia, in 2012, and the Master's degree and the Ph.D. degree in applied mathematics and computational science from King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, in 2013 and 2018, respectively.

In January 2019, I was a Postdoctoral Researcher at the Chair of Mathematics for Uncertainty Quantification at RWTH Aachen University, Aachen, Germany.

In October 2022, I was appointed Lecturer in Statistics at the School of Mathematics, Faculty of Engineering and Physical Sciences. I am 50% seconded, initially for two years, to work with the UK Met Office to influence and deliver high-impact research in the area of weather and climate science and services. This unique role aims to provide new links between the Met Office and the School of Mathematics.

I am Associate Editor for Statistics and Computing

Research interests

My research interests are mainly focused on developing computationally efficient Monte Carlo estimators for the estimation of challenging statistical quantities for various real-life applications. In particular, I am interested in using variance reduction techniques to efficiently estimate rare event problems in different applications/dynamics.

I am currently investigating a novel connection between importance sampling and stochastic optimal control for dynamics evolving according to stochastic differential equations (SDEs), McKean Vlasov SDEs, and stochastic reaction networks. This has several applications including weather forecasting, computational finance, pedestrian flow dynamics, and computational biology.

I am also interested in rare events simulation for static problems with an emphasis on applications in climate science (analysis and simulation of extreme and rare climatic events), and wireless communications.

Another topic of interest is to use techniques from stochastic optimal control to solve challenging real-life applications such as optimal inventory management for supply chains and optimized power procurement strategies for wireless networks powered by uncertain renewable energy.

Qualifications

• PhD in Applied Mathematics and Computational Science, KAUST
• MSc in Applied Mathematics and Computational Science, KAUST
• BSc in Polytechnic Engineering, Ecole Polytechnique de Tunisie

Professional memberships

• Fellow of The Higher Education Academy
• Society for Industrial and Applied Mathematics

Research groups and institutes

• Modern Applied Statistics
• Statistics
• Probability and Financial Mathematics
• Statistical Methodology and Probability

Current postgraduate researchers

• Mendrika Rakotomanga

Projects

<li><a href="//phd.leeds.ac.uk/project/2006-modelling-and-stochastic-simulation-of-supply-chains">Modelling and Stochastic Simulation of Supply Chains</a></li> <li><a href="//phd.leeds.ac.uk/project/1509-variance-reduction-techniques-for-rare-events-simulations">Variance Reduction Techniques for Rare Events Simulations</a></li>