Development of a digital twin model of the low voltage network regressed from smart-meter time series, constrained by physical laws and the network topology (physics informed AI). Application of this model to optimize the insertion of photovoltaic panels or the connection phase of clients.

Development of lightweight efficient Deep learning models for autonomous driving with tensorflow and pytorch:- Object detection (Yolo, Mask RCNN)- Image segmentation (PSP-Net, IC-Net)- Domain transfer learning (Adversarial networks)

My research focused on quantum dots integrated in photonic crystal circuits:- Design, and simulation of photonic crystal circuits (FDTD and FDFD modelling of Maxwell's equations).- Nano-fabrication in a clean room (SEM, RIE, ICP, AFM, PECVD) - Optical characterisation of optoelectronic circuits (using photoluminescence, time-resolved luminescence, photon correlations and the related statistical data analysis).