The continuous development process of artificial systems (e.g., software, critical infrastructure) and their interactions with their environments leads to a constant increase in complexity on various levels. Due to the diversity and opacity of interactions both within and outside these systems, it is increasingly challenging to fully anticipate adverse incidents and manage their effects. Therefore, the primary objective of the CORE group is to develop novel analytical approaches for assessing the complexity and resilience characteristics of man-made systems and developing strategies to enhance its performance.
Research
Within a highly interdisciplinary team, our research topics include (but are not limited to):
- Techniques for advancing machine learning capabilities, including preprocessing, processing, and post-processing.
- Enhancing transparency, interpretability, and explainability of Artificial Intelligence and Digital Twins
- Studying the underlying rules of natural and man-made systems to understand behaviors ranging from nonlinearity to multilayered interactions between different components. By deducing mechanisms that regulate biological systems, we provide new insights into assessing software aging and maintenance.
- Investigating and advancing methodological approaches in Information Theory and Complexity Science for multivariate time series analysis and complex matrices. The goal is to gain insights into the dynamics of various systems and to study underlying patterns for identifying errors, security risks, early warning signals, and enhance prediction accuracy of Machine Learning tasks.
- Exploring quantum-inspired machine learning methods for identifying abnormal system behavior in network structures and reducing functional risk.
The Complexity and Resilience Group participates in the following research projects:
EDIH innovATE
EDIH innovATE – The European Digital Innovation Hub for Agrifood, Timber and Energy
QCI-CAT
Deploying advanced national QCI systems and networks
PICUS
Integrative concept for data fusion and optimisation of forest fire monitoring processes
Beyond Coding
Software-Entwicklung der Zukunft
LivestockSense
Enhancing environmental sustainability of livestock farms by removing barriers for adoption of ICT technologies
G-STAR
Gesamtstaatliche Erfassung der Resilienz im Kontext komplexer Krisenszenarien
Joint Seminar Austria/Japan
Security and Resilience for P2P Energy Trading
Digital Pro Bootcamp
Cyber-Resilience in Medical Applications
DRIVER+
Driving Innovation in Crisis Management for European Resilience
is researcher at SBA Research.
is researcher at SBA Research.
leads the “Complexity and Resilience Research Group” (CORE) at SBA Research and is researcher at TU Wien and University of Vienna.
is researcher at SBA Research.
is researcher at SBA Research.
is researcher at SBA Research.
The following scientific partners and company partners are / have been working closely together with the Complexity and Resilience Group:
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Teaching
The Complexity and Resilience Group is planning teaching activities.
Bachelor | Master | PhD - Thesis Supervision
The CORE Research Group is supervising Bachelor, Master and PhD theses in the following areas.
- Understanding runtime system behaviour
- Understanding and Handling Complexity
- Management and Organisational Dynamic
More information about thesis topics here.
For further details please contact team lead Kevin Mallinger directly.
To contact the team, please reach out to the individual team members or to the team lead Kevin Mallinger.