Some aspects of my research work are presented below:
- Application of stochastic, risk-constrained and robust optimization methods to decision-making under uncertainty. Published extensively on the concept of 'smart grid option value' and currently extending my work to the field of decision-dependent uncertainty modelling.
- Development of novel decomposition schemes for very large-scale optimization problems. Published state-of-the-art methodologies for the decomposition of large design and operation problems using hierarchical approaches, Nested Benders, Stochastic Dual Dynamic Decomposition, multi-cut algorithm variants etc.
- Pioneering work on the use of machine learning for surrogate modelling of the dynamic behavior of complex systems. In this context, I have led critical work on the stability assessment of the pan-European electricity grid (iTesla project) and continue this research track in collaboration with the French Transmission System Operator RTE.
- Development of novel high-dimensional modelling frameworks based on vine copulas with applications to non-linear data-sets of >4000 variables.
- Novel Monte Carlo methods applied to the development of energy storage capacity credit methodologies.