Theory and Algorithms

Computer science is both an engineering science and a basic science. Thanks to this dual nature, it covers a variety of fundamental concepts including processes, computation, information and communication. Computer science theory is concerned with understanding, defining and analysing these concepts using formally proven guarantees. Theoretical insights are often highly relevant in practice (for instance, from algorithm theory) or even intrinsically necessary – from cryptography, for instance.  

 

 

 

 

Focal areas of theory research at the department include cryptography and algorithms and complexity, as well as discrete mathematics, estimation and optimisation. Some of this is conducted jointly with the Department of Mathematics.

Areas of research

algorithms, bioinformatics, combinatorics, complexity theory, computational science, cryptography, geometry, optimization, randomization & probabilistic methods

Computer science professor Bernd Gärtner

Bernd Gärtner
Titular Professor

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algorithms, combinatorics, geometry, optimization



Prof. Niao He

Niao He
Assistant Professor

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large-scale optimization, machine learning, reinforcement learning, probabilistic inference 

Professor Dennis Hofheinz

Dennis Hofheinz
Full Professor

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cryptography, information security, proof systems, algorithms, theoretical computer science

 

Prof. Dennis Komm

Dennis Komm
Associate Professor

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algorithm design and analysis, approximation and parametrisation, advice complexity, didactics and education

 

Prof. Rasmus Kyng

Rasmus Kyng
Assistant Professor

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algorithms, convex optimization, graph algorithms, numerical linear algebra, fine-grained complexity theory, random matrix theory
 

Computer science professor Ueli Maurer

Ueli Maurer
Full Professor

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cryptography, information security, theoretical computer science, information theory, discrete mathematics


Angelika Steger
Full Professor

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algorithms, combinatorics, randomization and probabilistic methods, combinatorial models for optimization

Computer science professor David Steurer

David Steurer
Associate Professor

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complexity theory, approximation algorithms, convex optimization, parameter estimation, tensor methods

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