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Next Lectures:
Helmut Bölcskei - The Mathematical Universe behind Deep Neural Networks
Monday, November 25th, 5:15 pm
Location: Große Aula, Raum E 120, 1. OG, Geschwister-Scholl-Platz 1, 80539 München, LMU München
This event is open to everyone, registration is not required.
Abstract
Deep neural networks have led to breakthrough results in numerous practical machine learning tasks. In this lecture, we will attempt a journey through the mathematical universe behind these practical successes, elucidating the theoretical underpinnings of deep neural networks in functional analysis, harmonic analysis, complex analysis, approximation theory, dynamical systems, Kolmogorov complexity, optimal transport, fractal geometry, mathematical logic, and automata theory.
Bio
Helmut Bölcskei is a professor of Mathematical Information Science at ETH Zurich. Since 2021 he has also been a Principal Investigator at the Lagrange Mathematics and Computing Research Center, Paris, France.
He received his degrees from Vienna University of Technology, Vienna, Austria, was a postdoctoral researcher in the Information Systems Laboratory, Department of Electrical Engineering, and in the Department of Statistics, Stanford University, Stanford, CA. He was in the founding team of Iospan Wireless Inc., a Silicon Valley-based startup company (acquired by Intel Corporation in 2002) specialized in multiple-input multiple-output (MIMO) wireless systems for high-speed Internet access, and was a co-founder of Celestrius AG, Zurich, Switzerland. He was a visiting researcher at Philips Research Laboratories Eindhoven, The Netherlands, ENST Paris, France, and the Heinrich Hertz Institute Berlin, Germany. His research interests are in applied mathematics, machine learning theory, mathematical signal processing, data science, and statistics.
He received the 2001 IEEE Signal Processing Society Young Author Best Paper Award, the 2006 IEEE Communications Society Leonard G. Abraham Best Paper Award, the 2010 Vodafone Innovations Award, the ETH “Golden Owl” Teaching Award, is a Fellow of the IEEE, a 2011 EURASIP Fellow, was a Distinguished Lecturer (2013-2014) of the IEEE Information Theory Society, an Erwin Schrödinger Fellow (1999-2001) of the Austrian National Science Foundation (FWF), was included in the 2014 Thomson Reuters List of Highly Cited Researchers in Computer Science, was the 2016 Padovani Lecturer of the IEEE Information Theory Society, and received a 2021 Rothschild Fellowship from the Isaac Newton Institute for Mathematical Sciences, Cambridge University, UK. He served as editor-in-chief of the IEEE Transactions on Information Theory and is the founding editor-in-chief of the Springer journal “Mathematical Foundations of Machine Learning”. He has been a delegate for faculty appointments of the president of ETH Zurich since 2008.
Dr. Scherer received his B.S. in Computer Science, M.S. and Ph.D. in Robotics from CMU in 2004, 2007, and 2010.
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