My research interests are mainly in the inter-disciplinary applications of data science (mathematical/statistical/machine-learning) techniques to the real-world problems, specifically in the areas of energy, water, climate change, extreme events, flood-risk and environmental impact assessment. I developed my research track record by leading and contributing several multi-disciplinary research involving the novel application of Mathematical/Statistical/AI techniques such as: Hidden-Markov Modelling, Stochastic Processes, Time series modelling, Uncertainty and Data Analysis, Complex Networks, Non-Linear Dynamical System, Bifurcation Analysis, Chaos and Machine-learning/DeepL.

I developed this track record through my association (either as Lead/CI/post-doc researcher) with several high-profile multidisciplinary research projects (e.g. EP/F038240/1, EP/I03534X/1, EP/K013513/1, EP/L000180/1, EP/N030419/1).

In addition to this, I have extensive experience in big data analytics and have excellent scientific programming skills (e.g. Python, R, Matlab, C, C++, FORTRAN, etc). My work has been documented in over 70 peer-reviewed inter-disciplinary research publications. Three of my outputs have won best paper awards and two won best presentation awards at high-profile international events.