Title: "Convergence proof for gradient descent optimization methods in the training of deep neural networks"
Biography: Arnulf Jentzen (*November 1983) is appointed as a full professor for applied mathematics at the University of Muenster (since 2019) and as a full professor for data science at the Chinese University of Hong Kong, Shenzhen (since 2021). In 2004 he started his undergraduate studies in mathematics (minor field of study: computer science) at Goethe University Frankfurt in Germany, in 2007 he received his diploma degree at this university, and in 2009 he completed his PhD in mathematics at this university. The core research topics of his research group are machine learning approximation algorithms, computational stochastics, numerical analysis for high dimensional partial differential equations (PDEs), stochastic analysis, and computational finance. He is particularly interested in deep learning based algorithms for high dimensional approximation problems and different kinds of differential equations. At the moment he serves as an associate or division editor for the Annals of Applied Probability (AAP, since 2019), for Communications in Computational Phyiscs (CiCP, since 2021s), for Communications in Mathematical Sciences (CMS, since 2015), for Discrete and Continuous Dynamical Systems Series B (DCDS-B, since 2018), for the Journal of Complexity (JoC, since 2016), for the Journal of Mathematical Analysis and Applications (JMAA, since 2014), for the SIAM / ASA Journal on Uncertainty Quantification (JUQ, since 2020), for the SIAM Journal on Scientific Computing (SISC, since 2020), for the SIAM Journal on Numerical Analysis (SINUM, since 2016), for the Journal Springer Nature Partial Differential Equations and Applications (PDEA, since 2019), and for the Journal of Applied Mathematics and Physics (ZAMP, since 2016). In 2020 he has been awarded the Felix Klein Prize from European Mathematical Society (EMS). Further details on the activies of his research group can be found at the webpage http://www.ajentzen.de.