His supervisors were two PR[AI]RIE chairs: Laurent Massoulié and Marc Lelarge.
The thesis studies the graph alignment problem, the noisy version of the graph isomorphism problem, which aims to find a matching between the nodes of two graphs which preserves most of the edges. Focusing on the planted version where the graphs are random, we are interested in understanding the fundamental information-theoretical limits for this problem, as well as designing and analyzing algorithms that are able to recover the underlying alignment in the data. For these algorithms, we give some theoretical high probability guarantees of the regime in which they succeed or fail.
For further info, and the manuscript, please visit https://lganassali.github.io/