HITS conducts basic research in the natural sciences, mathematics and computer science. The research areas range from molecular biology to astrophysics.
A strong focus is on the development of new theoretical and computational approaches to handling and interpreting rapidly increasing amounts of experimental, observational and simulated data. HITS researchers employ methods such as data mining and simulation, and they develop software and databases.
HITS strives for a long-term research agenda with projects that show high potential for significant results. We focus on a small number of challenging research fields in which our research is curiosity-driven and unhindered by disciplinary barriers.
Our research is interdisciplinary and cooperative. We collaborate intensively with other research institutions, universities and industry partners.
Furthermore, we aim to raise public awareness for the importance of science – especially data-driven science.
The AIN group develops new methods and tools to deal with the exponentially increasing amount of data in astronomy.
The CCC group uses state-of-the-art computational chemistry to explore and exploit diverse functional organic materials.
The CME group focuses on developing algorithms, computer architectures, and high-performance computing solutions for bioinformatics.
The CST group focuses on the theory and practice of forecasts as well as on spatial statistics.
The DMQ group uses stochastic mathematical models, high-performance computing, and hardware-aware computing to quantify the impact of uncertainties in large data sets.
The GRG group investigates various mathematical problems in the fields of geometry and topology, which involve the interplay between geometric spaces.
The MCM group focuses on the interactions of biomolecules. Research methods include interactive, web-based visualization tools and atomic-detail molecular simulations.
The MBM group focuses on deciphering how proteins have been designed to specifically respond to mechanical forces in the cellular environment or as a biomaterial.
The NLP group develops methods, algorithms, and tools for the automatic analysis of natural language.
The PSO group models thermonuclear explosions of white dwarf stars leading to the astronomical phenomenon of Type Ia supernovae.
The SDBV group improves data storage and the search for life science data, making storage, search, and processing simple to use for domain experts who are not computer scientists.