In 2022, the two courses will be given by :


Rebecca Willett (Chicago University) on "Regularization Induced by Neural Network Architectures"
Rebecca Willett

Rebecca Willett is Professor and Director of AI at the Data Science Institute of the University of Chicago. She is contributing to the mathematical foundations of machine learning and large-scale data science, with a special interest for cases where there exist some hidden structures. Her work lies at the intersection of high-dimensional statistics, inverse problems, network science and signal processing. She serves as an associate editor for the most renown journals in theses fields. Rebecca Willett has been awarded of an NSF CAREER Award 2007, and she has been named SIAM Fellow 2021, and IEEE Fellow 2022.

Richard Nickl (Cambridge University) on "Bayesian non-linear statistical inverse problems".
Richard Nicki


Richard Nickl is Professor at the University of Cambridge. His research contributions cover various areas of the fields of high-dimensional and non-parametric statistics. He serves as an associate editor for the most renown journals of these fields. Among his major recent contributions, Richard Nickl has developed a rigorous statistical theory for Bayesian methods for non-linear non-convex PDE-constrained inverse problems. He has been awarded by one ERC grant, the 2017 Ethel Newbold Prize of Bernoulli Society, the 2017 PROSE Award of the American Association of Publishers, and he is an invited speaker for ICM2022.