I am a fifth-year PhD student in the Statistics department at Stanford University, where I am lucky to be supervised by Professor Susan Holmes.
Prior to Stanford, I studied Applied Mathematics and Engineering at Ecole Polytechnique (France), where I received a Bachelor and Masters of Science.
My research interests lie in the analysis of structure and patterns in high-dimensional datasets, and in particular, in the analysis of graphs.
Indeed, from brain connectomics to cybersecurity, graphs appear as an indispensable paradigm for studying complex relationships between entities in a number of applications where the analysis of the system at the "atomic" node-level is either intractable or uninformative. However, graphs are non-Euclidean objects, for which there exists no standard statistical notion of mean, variance, etc. The definition of a principled framework for doing Statistics and Machine Learning on graphs is thus an active, open area of research, which I have begun exploring during my PhD.
I am especially interested in biomedical applications of this topic, and in particular, in brain connectomics – a developing field in neuroscience which strives to understand the functional and anatomical “wiring” of the brain and its association with cognitive processes and psychiatric diseases.