More informations are available on my personal website.
Short Bio
I completed my PhD in applied mathematics at the University of Caen Normandy in France, where I studied regularization methods for data completion problems in structural mechanics.
Following that, I worked on seismic data processing for imaging of bedrocks in a collaborative project between the French National Institute for Research in Digital Science and Technology (INRIA) in Paris and the French energy company (EDF).
Currently, I am a postdoctoral research fellow at UiO under the DSTrain programme, working with the DSB group on medical ultrasound elastography.
Research interests
Broadly speaking, I am interested in applied mathematics, with a particular focus on inverse problems and imaging. My focus is on developing non-invasive methods to recover incomplete or inaccessible information from a limited set of measurements. This often involves using non-destructive waves, which propagate through the medium and are affected by the structures they encounter, allowing us to extract valuable information about the internal composition of the medium they traverse.
With a background in mathematics, I tend to approach physical problems through mathematical modeling to better understand their underlying complexities. Recently, I've become particularly interested in full-waveform inversion as a quantitative imaging algorithm, which aims to align models with observed data through iterative optimization. I am also exploring the integration of physics-based simulations with machine learning models to accelerate the computationally intensive simulations of wavefield propagation.