Data science, the generation of knowledge from data, is gaining importance in an increasingly digitalized world. The methods used are numerous and range from the analysis of big data to state-of-the-art data mining and machine learning methods. This goes along with the increasing application of discrete and quantitative methods of applied mathematics and informatics. This includes the development and application of optimization models and methods for decision support.
Research Groups
Project Highlights
Given the extent of damage of heavy rainfall and the increased frequency of these events due to climate change, one of the key challenges in urban drainage systems is how to handle floods caused my heavy rain.
Within Prof. Thielen’s project “Incentive systems for communal flooding precautions (AKUT by its German initials)” innovative optimization models are developed to determine the best possible precaution concepts and the necessary incentives for their implementation with citizen participation.
This section of machine learning enables training of an artificial intelligence (AI) to independently solve a certain problem. This joint project of Prof. Burger and Prof. Grimm uses and expands this concept to support the planning process for synthesis of flow diagrams in process engineering. At this, the AI creates flow diagrams to given tasks and subsequently receives feedback which directs the learning process.
