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Felix Krahmer

Associate Professor · Optimization and Data Analysis

Germany

About

Prof. Dr. Felix Krahmer is an Associate Professor for Optimization and Data Analysis at the Department of Mathematics, Technical University of Munich (TUM). His research focuses on mathematical foundations of data science, with expertise in

Compressed Sensing
Unlimited Sampling
Quantization of Signals and Images
Neural Networks
Uncertainty Quantification
Low-Rank Recovery

He leads the Data Science research group within TUM's School of Computation, Information and Technology, collaborating with institutions like TU Berlin, RWTH Aachen, and Technion.

His recent publications span topics like

Robust blind deconvolution under adversarial noise
Kronecker-structured dimensionality reduction
Hysteresis in unlimited sampling systems
Efficient sparse FFT algorithms

Notable scientific awards include two August-Wilhelm-Scheer Visiting Professorships (2016, 2019) for hosting international collaborators.

Former and current students include

Olga Graf
Dominik Stöger
Claudio Verdun
Felipe Pagginelli Patricio
Juana Kostin

He has co-organized workshops at SAMPTA, Oberwolfach, and ISIT, serving as associate editor for journals including SIAM Journal on Matrix Analysis and Frontiers in Signal Processing.

Research fields

Optimization and Data Analysis Compressed Sensing Unlimited Sampling Quantization of Signals and Images Signal Processing Neural Networks Uncertainty Quantification Randomized Sensing Sparse Regularization Low-Rank Recovery

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Felix Krahmer

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