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The construction and analysis of algorithms and data structures is a basic and very important part of modern computer science. Its importance increases also by the rapid development of more powerful and faster computers. All computer programs can be described as algorithms that operate on a structured set of data, or as a concatenation of such algorithms. To construct a large program with a reasonable time and space consumption it is essential to have efficient solutions to the problem parts.
The main areas of research studied by the algorithm group fall into five mutually interrelated categories, namely computational geometry, geometric graph algorithms, parallel, distributed and sequential graph algorithms, computational biology, searching and sorting.
In the computer graphics group, we are doing research on and developing new algorithms for the creation of images from three-dimensional scene descriptions. We have a special focus on computer graphics for mobile devices, such as mobile phones. On those platforms the algorithms need to be very efficient both in terms of memory bandwidth and power, and implementations must be very small. This presents difficult challenges that we attack in our research. Another area of study is programming languages and software architectures suitable for computer graphics applications. We are also looking into algorithms for ray tracing, GPU architectures, graphics hardware, rasterization algorithms, shading languages, and collision detection.
Research in this field concentrates on different aspects of embedded computer systems design. It involves a number of areas, such as real-time systems, distributed processing, (discrete) system modeling and analysis, compilation techniques, program and model transformations, and optimization methods. The big challenge of this research is to find efficient methods and tools which can be used in industry to enhance a design process, make time-to-market shorter and improve overall quality of the final products.
Robots, and automation systems, are user-programmable equipment and mechatronic devices. Robotics and Automation involves designing and implementing intelligent machines which can do work too dirty, too dangerous, too precise or too tedious for humans (see IEEE-RAS.org).
Semantics is the study of meaning, and within computer science that is closely related to Artificial Intelligence (AI) and Natural Language Processing (NLP). We also apply semantic techniques in robotics and automation, to facilitate high-level interfacing and to better support human-robot interaction. Combining semantic technologies with industrial automation is one of our research topics, thus aiming at semantic systems.
That wide spectrum of topics, ranging from mechatronics and control software to the semantic web technologies and natural language dialogs, forms the field of Robotics and Semantic Systems (RSS). We specialize on some key specific topics, creating a unique research profile by an emphasis on applicability and system aspect.
We do experimental research on the development of new tools, languages, and methods for software development. Our ultimate goal is to find new ways of making software development more efficient. Example areas we work with include compilation of object-oriented languages, runtime systems, real-time programming, configuration management, pervasive systems, metaprogramming tools, integrated development environments, domain-specific languages, agile methodology, software architecture and design.
We collaborate with industry and society to get realistic scenarios for application of new ideas. Example application areas include mobile devices, embedded systems, health care, and industrial robotics.
We focus on software platform management in product line engineering of embedded systems. Current areas of research include Requirements Engineering, Verification & Validation, Software Process Quality, System Safety, and Software Management. We also study aspects of the Digital Society in cross faculty settings. The research is conducted with close industry contacts using Empirical Methods, including surveys, experiments and case studies.
We teach undergraduate and graduate courses in software engineering, which provide knowledge and understanding of large scale industry contexts.
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Last updated: 2013-05-28