Research Interests

I work mainly in the field of functional data analysis (FDA), which is a sub-field of mathematical statistics, centered around the problem of statistical inference on the law of a continuous-time random process given multiple realizations of such a process. I am particularly interested in functional data on multi-dimensional domains, where the random process is not only a function of time but also e.g. of space. My research focuses on methodological aspects, but computational costs and numerical aspects naturally enter into consideration due to the size and continuity of multi-dimensional functional data. In another line of research, I develop optimization algorithms for NP-hard versions of principal component analysis (PCA) such as matrix completion, robust PCA or sparse PCA. The intersection between my two main lines of research is the concept of low-rankness (in different forms), which I consider to be powerful and useful in many applied problems.

Work in Progress

Publications

Software

surfcov package

cerss package