
The APL section does research in a wide range of areas related to algorithms, programming languages and systems. In the area of algorithms, our research covers discrete optimization algorithms inspired by practical problems in bioinformatics, electronic chip design and logistics. In the area of programming languages, our research covers theoretical and practical research of programming languages with a focus on automatic program optimization, analysis and transformation.
HIPERFIT is a joint research center addressing the simultaneous challenges of high transparency, high computational performance and high productivity in finance, employing an integrated approach of financial mathematics, domain specific languages, parallel functional programming, and high-performance systems.
BARC is a center for fundamental algorithmic research. Their aim is to attract top talents from around the world to an ambitious, creative, collaborative, and fun environment. Using the power of mathematics they strive to create fundamental breakthroughs in algorithmic thinking, typically disseminated in top venues such as STOC, FOCS, and SODA.
EADS is a centre for fundamental research, created to search for the outer limits of what computers can handle when it comes to principles of chance.
The mission of the Performance Engineering Lab is to educate elite programmers and to do high-quality research related to any aspect of programming, performance programming in particular.
Study of reversible computing models from the perspective of programming languages and logic design.
Computational Biology is concerned with ''development and application of data-analytical and theoretical methods, mathematical modelling and computational simulation techniques to the study of biologial, behavioral, and social systems.
Our work will contribute to the effective use of regular expressions without requiring users to understand the mechanics of the underlying computer science theory.
The Data Management Systems (DMS) group conducts research in areas emerging with new challenges in data management.