Study level

  • PhD
  • Master of Philosophy
  • Honours

Faculty/School

Faculty of Science

School of Information Systems

Topic status

We're looking for students to study this topic.

Research centre

Energy Transition Centre

Supervisors

Dr Kenan Degirmenci
Position
Course Coordinator
Division / Faculty
Faculty of Science

Overview

The transition toward a more sustainable energy system is generating vast volumes of data from distributed sources such as smart meters, energy sensors, and user-end devices. Energy informatics highlights the crucial role of information systems in optimising both energy supply and demand (Watson et al., 2010). In this project, we explore how cognitive computing systems (CCS), integrating artificial intelligence (AI), cognitive psychology, and neurobiology, can strategically transform energy informatics by creating adaptive, explainable, and human-aligned energy solutions.

Leveraging advances in CCS such as neuroadaptive interfaces and concept neuron networks (Tuczek et al., 2025), the project investigates how these technologies can improve real-time decision-making, user-system interactions, and energy efficiency in complex systems like smart grids or virtual power plants. Managing energy system intermittency increasingly depends on the ability to dynamically balance complex, interwoven decisions, such as when to defer loads, trade consumption rights, adjust prices, or utilise storage, requiring solutions that are both responsive and explainable (Watson et al., 2022).

In this project, we aim to provide strategic design principles for deploying CCS in energy informatics to enable eco-effective behaviour and sustainable infrastructure transformation. This project is part of the Research Group Behavioural Energy Analytics & Modelling (BEAM), based in the School of Information Systems.

References

  • Tuczek, M., Degirmenci, K., Song, Y., Desouza, K. C., Breitner, M. H., & Watson, R. T. 2025. Strategic implications of cognitive computing in IS: addressing AI fragmentation through knowledge similarity transformation. Journal of Strategic Information Systems, 34(2), pp. 1-20. https://doi.org/10.1016/j.jsis.2025.101908
  • Watson, R. T., Boudreau, M.-C., & Chen, A. J. 2010. Information systems and environmentally sustainable development: Energy informatics and new directions for the IS community. MIS Quarterly, 34(1), pp. 23-38. https://doi.org/10.2307/20721413
  • Watson, R. T., Ketter, W., Recker, J., & Seidel, S. 2022. Sustainable energy transition: Intermittency policy based on digital mirror actions. Journal of the Association for Information Systems, 23(3), pp. 631-638. https://doi.org/10.17705/1jais.00752

Research activities

  • Develop a framework for user–system interaction in energy management systems enhanced by CCS.
  • Analyse neuroadaptive feedback mechanisms to influence energy behaviour.
  • Investigate strategic decision-making enhancements in decentralised energy systems using CCS.
  • Apply explainable AI principles to energy informatics to increase trust and transparency.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

Contact

Contact the supervisor for more information.