Research

My research interests in the field of Artificial Intelligence (AI) include, but are not limited to:

A comprehensive list of papers I co-authored is provided by the DBLP Bibliography. Most of them are available for download from the website of the Knowledge Processing and Information Systems group at the University of Potsdam. Some bibliographic metrics are summarized by Google Scholar.

My research paved the way to the state-of-the-art systems for Answer Set Programming, a practically oriented subarea of Knowledge Representation and Reasoning (KR&R), developed in the Potassco project. For learning more about these declarative problem solving systems, I recommend the online documentation, as well as the following papers for further details or citations, respectively:

Taking advantage of general-purpose solving systems to build effective declarative solutions for challenging applications constitutes another main target of my research. Some of my recent work on applications addressing production planning, logistics systems, personnel scheduling and product configuration is presented in the following papers:

In my current research I strive to gear up general-purpose solving systems for performing combinatorial search and optimization in demanding application environments, where concepts like resource handling, real-time requirements and dynamic user interaction play a crucial role. By investigating and developing innovative solutions for respective model scenarios in close collaboration with domain experts from research and industry, I envisage to achieve immediate practical benefits and general scientific advances at the same time. As a primary research objective I aim at pushing the Industry 4.0 transformation to managing modern production processes in a much more integrated, efficient and adaptive way than achievable with conventional methods only.


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Last modified on 21 September 2018