Colloquium Computer Science - Dr. Andreas Metzger University of Duisburg

Title: Data-driven AI for Self-adaptive Software Systems

Abstract:

A self-adaptive software system is capable of modifying its own structure and behaviour at runtime based on its perception of the environment, of itself and of its requirements. As an example, a self-adaptive web application may deactivate its resource-intensive recommender engine in order to maintain its performance requirements when faced with a sudden increase in workload.

This talk will explore the opportunities that data-driven AI offers in building self-adaptive software systems. On the one hand, it will present how machine learning ensembles support accurate and timely proactive decision making for business process management. On the other hand, it will present how reinforcement learning may be employed to build software systems that dynamically improve themselves during operations. The talk closes with a critical look at the challenges entailed in delivering trustworthy AI-based software systems.

Bio :

Dr. Andreas Metzger is senior academic councillor at the University of Duisburg-Essen and head of adaptive systems and big data applications at paluno, the Ruhr Institute for Software Technology. Andreas is steering committee vice-chair of the European Technology Platform on Software, Services, Cloud and Data (NESSI) and deputy secretary general of the EU Big Data Value Association (BDVA). His background and research interests are software engineering for data-intensive and self-adaptive systems, in particular exploring the use of machine learning and artificial intelligence technologies for proactive and self-learning systems.