Data & Information
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Whether in logistics, medicine or mobile communications - many applications give rise to data sets of increasing size. In order to analyze and use that amount of data efficiently, new mathematical tools are required.
At the TUM Department of Mathematics, we develop and research methods for data processing and extract relevant information, specifically addressing the challenges of large data sets. Mathematics in Data Science enables the creation of forecasts, the conservation of resources and the reduction of costs in many areas of application.
Research areas
Different groups in our Department study Data & Information from the viewpoints of
- optimization,
- probability and statistics,
- applied harmonic analysis,
- computational topology, and
- quantum information theory.
Professors
- Ulrich Bauer
- Folkmar Bornemann
- Claudia Czado
- Mathias Drton
- Massimo Fornasier
- Claudia Klüppelberg
- Robert König
- Felix Krahmer
- Fabian Theis
- Michael Ulbrich
- Elisabeth Ullmann
- Michael Wolf
- Johannes Zimmer
Related research groups
Research News
Munich Data Science Institute takes off
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One World Dynamics
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"scVelo" predicts cell development
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SIAM Student Paper Prize für Jonas Latz
Former TUM student Dr. Jonas Latz receives the SIAM Student Paper Prize 2020 for his paper "On the Well-posedness of Bayesian Inverse Problems". The prize is awarded for the best papers by student authors.
Model for a secure contact tracing app
In the fight against Covid-19, the interdisciplinary research team ContacTUM has developed a model for a secure contact tracing app. Simulations should clarify whether the app can actually slow the spread of the corona virus.
Award for Dr. Dominik Stöger
Our former doctoral student Dr. Dominik Stöger receives the Dr.-Klaus-Körper-Prize 2020 of the GAMM for his outstanding dissertation on "Bilinear Compressed Sensing".
Drones can "hear" walls
Kann eine Drohne mithilfe von Schallwellen Wände und andere ebene Flächen orten? Dass das funktioniert, haben TUM-Professor Gregor Kemper und Professor Mireille Boutin von der Purdue University in Indiana mathematisch bewiesen.
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Are democratic elections always fair? Do the results really represent the will of the people? TUM Professor Peter Gritzmann reveals in the video on how mathematical methods can improve voting systems.