Artificial intelligence and deep learning are transforming photonics by enabling the modeling of complex light-matter interactions, the design of advanced photonic structures, and the extraction of meaningful signals from high-dimensional data. In our group, we apply deep learning to ultrashort laser pulse characterization and to the data-driven design and optimisation of plasmonic and nanophotonic structures.
The ability to generate and control light at extreme timescales opens a unique window into the fastest processes in nature, from electron dynamics in atoms and molecules to energy transfer in materials. We develop theoretical models and numerical tools to describe and optimise these phenomena, working in close collaboration with leading experimental laboratories worldwide.
When light interacts with matter, it triggers a rich cascade of electronic and structural responses — from the excitation of molecular orbitals to ultrafast energy redistribution in complex nanomaterials. We investigate these processes across scales, combining quantum chemical modeling with time-resolved spectroscopy, and exploring how nanophotonic environments can be engineered to control the fate of excited states.
We develop novel approaches for fabricating dielectric and metallic nanostructured films, and investigate their fundamental optical and plasmonic properties through a combination of experiments and numerical simulations. Fabrication and optical physics are two sides of the same coin: nanostructure architecture is engineered to achieve targeted plasmonic responses, while optical studies feed back into the next generation of designs.
Plasmonic nanostructures concentrate electromagnetic fields at the nanoscale, dramatically amplifying the interaction between light and matter in their vicinity. We exploit these properties to develop high-sensitivity sensing platforms for environmental and biomedical analytes, and to engineer the emission properties of fluorescent systems — with a longer-term vision of integrating plasmonic elements into functional photonic devices.