# Francqui Lecture Series Prof. Dr. Gitta Kutyniok

It was a great honor for the Department of Mathematics and Data Science from the VUB to welcome Prof. Dr. Gitta Kutyniok as a Francqui Chair holder.

Prof. Kutyniok is renowned for her mathematical approaches to solve problems from data science which she tackles with applied harmonic analysis, approximation theory, compressed sensing, frame theory, and functional analysis. She is well-known for developing the theory of shearlets, a natural extension of wavelets, back in 2006 and now concentrates, amongst others, on the mathematical foundations of machine learning. Her application domains include medicine such as magnetic resonance imaging, known as MRI, as well as telecommunication such as massive MIMO.

Prof. Kutyniok obtained her degree in mathematics and computer science and her PhD in mathematics at Paderborn University in Germany. She has held positions at Georgia Institute of Technology, the University of Giessen, Osnabruck, Washington University in St. Louis, Princeton, Stanford and Yale University.

She was the Emmy-Noether Lecturer of the German Mathematical Society in 2013 and became a member of the Berlin-Brandenburg Academy of Sciences and Humanities in 2016. In 2019 she was named a SIAM Fellow "for contributions to applied harmonic analysis, compressed sensing, and imaging sciences". Since 2011 she was Einstein Professor of Mathematics and a professor of computer science and electrical engineering at the Technical University of Berlin. Since the 1st of October 2020 she is professor in Mathematical Data Science and Artificial Intelligence at the University of Munich (LMU). She will be a plenary speaker at the eighth European Congress of Mathematics in Slovenia in 2021.

On the 30th November she gave her Inaugural lecture entitled

DEEP LEARNING MEETS MODELLING: TAKING THE BEST OUT OF BOTH WORLDS.

In this one hour talk she highlighted the pros and the cons of pure model-based approaches at one hand and pure data-based methodologies on the other hand and explain how both approaches can benefit from one another when combining them. Focus is on the inverse problem of (limited-angle) computed tomography.

The inaugural lecture was followed by four course lectures delving deeper:

For more information, contact Ann Dooms - Promotor of the Francqui Chair.

Sponsored by the Francqui Foundation.