Felix Krahmer

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.