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CORE

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:

Beyond Coding

Software-Entwicklung der Zukunft

Beyond Coding – Software-Entwicklung der Zukunft – focuses on two key competencies of software developers of… Read More

LivestockSense

Enhancing environmental sustainability of livestock farms by removing barriers for adoption of ICT technologies

The development of sustainable animal husbandry requires the removal of socio-economic and cultural barriers preventing… Read More

PICUS

Integrative concept for data fusion and optimisation of forest fire monitoring processes

Overview Forest fire monitoring has undergone a major technological shift in recent years through the… Read More

DRIVER+

Driving Innovation in Crisis Management for European Resilience

DRIVER+ is an ambitious pan-European project tasked with supporting the capability development of Crisis Management… Read More

is a FEMtech intern and 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.

Consulting Area

Kevin’s main responsibilities are in the area of project management, development of new business areas and strategic alliances, communication to the management board, organization and coordination of resilience workshops as well as applied resilience research.

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:


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.