Dr.-Ing. Marcus Grum's research group, entitled "AI-based System Design", is concerned with the question of how best to conceptualize, methodically design, systematically guide generalization, and disseminate artificial intelligence in systems such as ERP systems, control and management systems, software platforms, and production machines.

Neural Process Modeling Research A novel deep learning analytics is explored that reveals knowledge generation in neural networks and uses models to clarify how AI-based systems behave. It enables, for example, rapid corrective action for behavior control.	Neural Process Simulation Research A novel simulation technique is explored that simulates control strategies of complex industrial processes and incorporates predictive models to estimate neural models.	Neural Process Optimization Research A novel form of Deep Learning is being explored that brings about changes in arbitrarily complex processes and leads to improved business performance.
Research on AI-based system creation A novel modeling technique is explored that creates arbitrary systems based on data and artificial intelligence. It enables the autonomous evolution of systems that adapt to environmental changes.	Research on the evaluation of AI-based systems A new type of intelligence assessment is being explored that will allow AI performance to be analyzed and pedagogically-valuable interventions to be derived and the consequences of corrective actions to be assessed.	Research on the management of AI-based systems A novel management approach is being explored that enables the controlled modification of arbitrarily complex intelligent systems, leading to a targeted increase in business performance.

Research questions include:

• How can human and artificial process participants interact efficiently?
• How can knowledge be recognized and used in artificial systems?
• Wie kann ich die Entwicklung eines erfahrungsbasierten KI-System steuern?
• How can I unlearn learned patterns and behavioral routines from artificial agents?
• How can an a priori specified behavior be specifically taught to an artificial agent?
• How can existing industrial equipment and computer systems benefit from the use of AI?
• How should risks and limitations of AI deployment be handled?
• How should companies design their IT infrastructure and organization to be able to achieve competitive advantages using AI?
• How can a commissioning process of AI in production or for process control be designed to be efficient and plannable?

Bring intelligence to your systems:

• Workshops to develop implementation plans, AI integration strategies, and AI business model development.
• AI implementation education and training
• Structuring of the AI management
  
• Peptalks, keynotes and presentations on AI
  

Analyze and evaluate your systems to the levels of an AI foundation.

• Creation of AI product analyses
• Conducting AI market studies
• Deep-dive into your implemented AI, analysis and troubleshooting.
• Test procedures and quality assurance of intelligent systems
• Efficiency and sustainability analysis of Green-AI
  

Simulation of your systems on different levels of demonstrators

• Virtual and computer based
• Lego EV3 based
• Fischertechnik-based
• Industry 4.0-based
• Real productive environments
  

We are looking for cooperation with you

• Financed theses with industry and companies (bachelor, master, doctorate)
• Finanzierte studentische Projekte für Einstiegsstudien (Machbarkeitsstudien, Designprojekte)
• Contract research by companies focused on your unique AI needs.
• Joint research with companies and universities, e.g. ZIM- or BMBF-funded research projects
• Basic research with partner universities
  

Please contact marcus.grum@uni-potsdam.de for more information, visit us in our AI Lab, or take a look at AI examples: Link.