The CSH is a joint venture of researchers at the University of Hohenheim which aims at intensifying the exchange and cooperation across faculties and institutes to concentrate (combine) domain knowledge and methodological expertise in the fields of artificial intelligence (AI), data science as well as scientific computing.  

In that, the CSH promotes innovative and transdisciplinary research and teaching and actively contributes to the university-wide topic “digital transformation”:

• In research: Members of the CSH meet regularly in the CSH Seminar to present their current research and to exchange ideas. By combining domain knowledge from various disciplines with methodological expertise, it aims to help identify opportunities for cooperation and synergies for future research activities.

• In teaching: Extra-curricular courses developed by the CSH contribute to increasing the “Data Literacy” of our students in general and, with regard to AI and data science competencies in particular. In this way, the CSH complements the qualification profiles in a sustainable fashion.

Cooperation across institutes and faculties is furthermore promoted by the planned relocation of parts of the participating departments in the building Steckfeldstr. 2, once the renovation works are finished.

“Research needs creativity, spontaneity, impulses and expert feedback. With the Computational Science Hub, we will create an environment where researchers from all kinds of scientific areas that work with similar methods can come together, work on joint projects and inspire each other.” (Robert Jung, Spokesman of the CSH in an interview with the Hohenheimer Online Kurier on January 30, 2018)

The CSH is a platform where scientists from all three faculties (agricultural sciences, natural sciences, business, economics and social sciences), whose research involves processing and analysis of large data sets, modelling and simulation of complex systems, development of mathematical and statistical methods for data analysis or computational biology, can exchange their knowledge and expertise in the context of research and teaching. The aim is to strengthen the connections among scientists across faculties and, particularly, to combine domain knowledge from various disciplines with profound methodological expertise from “computational science” in order to promote innovative and transdisciplinary research and teaching at the University of Hohenheim.

In line with this idea, it is planned to locate parts of the participating institutes and departments - today spread over the campus - in one building in Steckfeldstr. 2. By bundling of competences and expertise in the development and application of data-intensive methods in one single place, the CSH will help create research impulses as well as new, state-of-the-art teaching concepts.

In this respect, the CSH actively contributes to the university-wide research topic “digital transformation”.

The scientists involved with the CSH initiative have domain knowledge in the fields: 

• Financial and commodity markets,
• innovation and sustainability,
• crop science and biology,
• digital agricultural science and diffusion processes,

as well as diverse and complementary methodological expertise in:

• Agent-based modeling (ABM),
• digital twinning,
• Microeconometrics (particularly quantitative evaluation methods for evidence based decision making),
• network analysis,
• quantitative text analysis and text mining,
• Statistical learning,
• design of experiments, and
• time series econometrics.

Apart from the institutes and departments involved with the CSH initiative, the Module “Data and Statistical Consulting (DSC)” of the Core Facility Hohenheim will be located at Steckfeldstraße 2. The module provides various services:

• Providing access to commercial and official economic and financial data sources (e.g. Refinitiv EIKON, CRSP, WRDS).

• Scientific counceling regarding statistical and econometric questions and the application of quantitative empirical methods,

• as well as support during all stages of empirical research projects, particularly in business, economics and the social sciences.