This project asks how quantum and hybrid quantum-classical optimisation can be used not just to solve energy management problems more efficiently, but to solve them in ways that are fair, transparent, and usable by real people. The student will build simplified sustainable energy scheduling and resource allocation models as QUBO problems, then solve them with classical and quantum-inspired methods using Qiskit.
Honours and Masters project
Displaying 1 - 10 of 287 honours projects.
Cybersecurity, Privacy and Cryptography in the Quantum Age
Motivation: The Unseen Bedrock of Modern Life
Cybersecurity and cryptography are the invisible, essential foundations of the modern digital world. Every day, billions of transactions and communications rely on complex mathematical puzzles to ensure confidentiality, integrity, authenticity, privacy and even more security features.
Bioinformatics analysis of spatial data in congenital heart diseases
Congenital heart disease affects 1 in 100 babies. Spatial gene expression patterns are critical to understand how the heart develops and what underlying genetic patterns are behind heart malformation. High-throughput spatial temporal data have been recently generated with spatial transcriptomics technologies. Capitalising on these rich datasets, we aim to build a custom analysis workflow in which the cells are profiled with precise spatial gene expression information. The student will provide fundamental contribution to of this project, by:
An Explainable Epidemiology System for Vaccine Safety and Proactive Care
This project aims to develop an explainable epidemiology system that combines generative AI, biostatistics, and epidemiological reasoning to support healthcare analysis and decision-making. The system will take structured health data as input, analyse it multimodally, and build a knowledge base that can be queried by epidemiologists and health researchers.
Quantifying superintelligence - anticipating and possibly avoiding loss of control
Discussion of dangers of artificial intelligence (or artificial superintelligence, ASI) being an ambitious subordinate and ultimately taking over control from humans goes back at least as far as R J Solomonoff (1967). R J Solomonoff (1985) gives an approximate time-frame in which this might occur.
Designing Human-Centred Digital Twins for Reliable and Resilient Energy Networks
Future electricity networks are becoming increasingly complex due to the rapid growth of distributed energy resources (DERs), batteries, renewable generation and intelligent infrastructure. Although modern networks collect large volumes of operational, asset and maintenance data, this information is often distributed across multiple systems, making it difficult for engineers and operators to understand the true reliability and resilience of the network or identify emerging risks before failures occur.
Deep Self-Supervised Learning of Bayesian Network Structures through Graph and Data Masking
Bayesian Networks (BNs) are widely used for modelling uncertainty and causal relationships in domains such as healthcare, finance, cyber security and decision support. However, learning the optimal BN structure directly from observational data remains computationally challenging due to the super-exponential search space of possible graphs.
Quantum computing approach for Bayesian network inference under realistic assumptions
Bayesian network (BN) inference—computing posterior probabilities given evidence—is a core task in probabilistic reasoning, but it becomes computationally expensive as networks grow in size or treewidth increases. Quantum-accelerated BN inference explores whether quantum algorithms and quantum circuit representations can provide practical advantages for approximate inference and sampling, while still making realistic assumptions about data access, noise, and limited quantum resources.