ZOMEGA Research Group
ZOMEGA Research Group
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The ZOMEGA research group brings together optimisation, AI, and quantum computing to power informed, uncertainty-aware decision-making for the net-zero energy transition.
Check the available PhD positions in the ZOMEGA group.
Research highlights
Research highlights
Long-term integrated investment, retrofit and abandonment planning of the European multi-energy-carrier system
Quantum computing and stochastic optimisation
Quantum computing and stochastic optimisation
Benchmarking quantum computing solvers with classical solvers
Using hybrid quantum-classical solver for solving unit commitment problems
Quantum computing for stochastic optimisation
papers: [1]
Group members
Group members
PhD students
PhD students
Ezra Daniels, University of Southampton (September 2025 - , SustAI CDT funded)
Topic: Machine learning enhanced solution algorithms for large-scale stochastic energy system planning.
Co-supervisors: Professor Christine Currie (University of Southampton), Professor Miguel Anjos (University of Edinburgh), Associate Professor Jesse D. Jenkins (Princeton University), Dr Filippo Pecci (CMCC).
Kyle McDonald, University of Southampton (September 2025 - , Maths School funded)
Topic: Quantum computing for large-scale stochastic optimisation in energy system planning.
Co-supervisors: Dr Stefano Cipolla and Dr David Bernal Neira (Purdue University).
Kristine Schüller, Norwegian University of Science and Technology (August 2024 -, Norwegian Research Council funded)
Topic: New methods for analyzing a 100% renewable Nordic electricity system.
Co-supervisor with Professor Hossein Farahmand (Norwegian University of Science and Technology) and Dr Arild Helseth (SINTEF Energy Research).
Benjamin Mitterrutzner, Norwegian University of Science and Technology (January 2025 - , LowEmission Research Centre funded)
Topic: Integrated North Sea energy system planning and decarbonisation.
co-supervisor with Professor Asgeir Tomasgard (Norwegian University of Science and Technology) and Dr Brage Rugstad Knudsen (SINTEF Energy Research).
Visiting students
Visiting students
Gabriele Sormani, Università degli Studi di Milano-Bicocca (10 March-31 July 2025)
MSc thesis topic: Leveraging neural network surrogate models for the efficient solution of multi-horizon stochastic programming.
Co-supervisor with Professor Enza Messina.
Gallery
Gallery
2025 winter (left to right: Selin, Kyle, Stefano, Ezra, and Hongyu)
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