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The Institute of Theoretical Computer Science is a competence center for the areas:
- algorithms and datastructures
- theory of combinatorial algorithms
- combinatorial structures and algorithms
- information security and cryptography
- quantum information
- MOSAIC Group: MOdels, Simulations, and Algorithms for Interdisciplinary Computing
- complexity and algorithms
Mission statements of the groups |
Informationsecurity and Cryptography
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Information is becoming a crucial if not the most
important resource of the economy and the society at large. Information
differs radically from other resources; for
instance, it can be copied without cost, it can be communicated at the
speed of light, and it can be destroyed without
leaving traces. This poses new challenges for the protection of this
new resource and of intellectual property in general. Information security,
in particular cryptography, is an enabling technology that is vital for
the development of the information society. Our missions are
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MOSAIC Group
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The research objective of our group is to develop and
apply theories and algorithms that are required for analysis, modeling,
and simulation of complex real-world systems.
“Complex†refers to the fact that the considered systems are dominated by geometric shape complexity (pre-fractal domains), unsteady stochastics, non-ergodic noise, high dimensionality, non-linearities, strong coupling, or the simultaneous presence of multiple time and length scales. Such systems constitute challenging applications for computational methods, and frequently require novel approaches to forward our understanding. We focus on systems that are of considerable interest in a natural, social, or engineering science. Success in those areas of application depends on the ability to develop concepts from Computer Science. Our main area of application is biology. This is motivated from both sides. The considered systems in modern biology are increasingly complex and foster the development of novel computational methods. Conversely, computational analysis, modeling, and simulation are of growing importance to interpret the large amounts of quantitative experimental data, reverse-engineer large dynamic systems, and enable unbiased assays with high statistical significance and reproducibility. The developed computational techniques are however applicable to a wider range of disciplines. We conceive of future collaborations with social, financial, and engineering sciences, as well as industrial research projects. The conducted projects are equally moving the frontiers in both Computer Science and the respective field of application. We aim at establishing computational methods as an integral part of applied and empirical sciences, forming a closed loop with experiments and hypothesis-driven reasoning
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Combinatorial Structures and Algorithms |
The main research interests of our group lie in the areas of combinatorial structures and algorithms, discrete mathematics, and combinatorial optimization. In particular we are interested in probabilistic methods, random graphs and algorithms, graph theory, and combinatorics. In addition to our theoretical work we select every few years a new "challenge" that allows us to demonstrate, use, and improve methods from modern theoretical computer science by working on a challenging "real world" application, see here for details. |
Theory of Combinatorial Algorithms |
Our goals are to provide good teaching for the students, a fruitful research environment for Ph.D. students and to achieve scientific findings (Erkenntnisgewinn) to be published in leading journals and conferences of theoretical computer science and discrete mathematics, the areas of our interest. |
Algorithms, Data Structures, and Applications |
We feel that algorithms research benefits from a certain breadth of topics, and we have been aiming to cover that breadth in a particular way that we want to continue to explore. In terms of computer science methods, our interest ranges from hard combinatorial and geometric optimization problems across data structures for large data sets and complex operations to distributed data handling and processing. In terms of application scenarios, we plan to continue the study of transportation problems such as railway optimization and control; of mobile phone antenna optimization problems such as placement, frequency assignment, and adaptivity; of proteomics problems such as database search and data analysis problems; of web related problems such as fault tolerant data handling and processing in a large network. All of these problems will be studied under a variety of conditions and objectives. In terms of mode of operation, we feel that it is important to be part of a research effort already in the modelling phase, carry all the way through the abstraction and solution phase to the phase of implementing and experimenting with algorithms and data structures. We are aware of the danger inherent in such an approach: Too much breadth certainly comes with a lack of depth, and too little breadth leads to a lack of cross-fertilizing experience. Our goal is to balance both in a way that allows us to do fundamental research and application development at the same time, and not disregard the area in between. |
Quantum Information |
We study quantum-physical phenomena from an information-theoretic
viewpoint. The motivation for this is two-fold: First, the perspective
of information has often proven to be the right one by leading to deeper
insight into physical phenomena. Second, we are interested in
information-processing tasks that only become possible with the help of
quantum physics. In this sense, our research has both science and
engineering motivation, goals, and characteristics.
Specifically, We are interested in quantum information processing, cryptography, and information theory. Our research also focuses on connections between these areas: What are the consequences of quantum-physical phenomena, such as entanglement or non-locality, for cryptography and information processing, e.g., communication complexity? Can we learn more about physical laws by studying them from an information-theoretic viewpoint? |
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