Honours and Minor Thesis projects

Freedom of Information is an important tool for investigating a public authority or organisation. Subject to certain conditions, it creates an obligation to provide recorded information, provided an organisation is a public authority.

I am interested in supervising projects that make use of Freedom of Information as a tool for investigating information management practices within public-sector organisations. For example, this might include information security, policies around information retention, or any other topic that can be investigated using Freedom of Information.

In situ analysis of complex biochemical metrices, such as microbial fermentation products, has drawn substantial research interests in recent years. Compared to the commonly used chemical analysis technique, spectroscopic analysis has great potential for this purpose due to its advantages of being rapid, contactless, lossless, and solvent-free. The major obstacle for the further application of the spectroscopic technique in the analysis of biochemical samples is the lack of customized data mining methods for the highly complicated spectral signal of the organic mixtures.

Using relevant available data-sets, we compare appliance usage across households of different demographics.  We then use machine learning techniques to infer how different households use different appliances at different times, resulting in diverse energy consumption behaviours. 

Climate change will affect us all, and we have to do everything we can to minimize the magnitude of change. Investments in renewable generation help to reduce the impact of energy usage on the supply side, but that will not get us all the way there, especially in the near term. Consumers will also have to become much more efficient with their energy use.

Behavioural manifestations of epileptic seizures (ESs) and certain non-epileptic seizures (psychogenic non-epileptic seizures, or PNESs) have considerable overlap, and so discerning between these solely based on clinical criteria is difficult.  Video EEG (electroencephalogram) monitoring (VEM) has high resource demands and is also expensive.  We endeavour to classify seizures based on non-invasive measures.

Verifiable Dynamic Searchable Symmetric Encryption (VDSSE) enables users to securely outsource databases (document sets) to cloud servers and perform searches and updates. The verifiability property prevents users from accepting incorrect search results returned by a malicious server. However, the community currently only focuses on preventing malicious behavior from the server but ignores incorrect updates from the client, which are very likely to happen in multi-user settings. Indeed most existing VDSSE schemes are not sufficient to tolerate incorrect updates from users. For instance,…

The security threat by quantum computing to almost all currently used digital signatures was triggered by the discovery of Shor’s quantum algorithm, which efficiently breaks the two problems underlying the security of these schemes, namely integer factoring, and elliptic curve discrete logarithms (ECDLP). When quantum computers become widespread, all security for the current digital signatures that are widely used to secure a wide range of systems is lost.

This multidisciplinary project combines cutting-edge Natural Language Processing (NLP), Chinese Studies and Political Science. The project aims to develop a deeper understanding of how official discourse has developed throughout the history of the People’s Republic of China. The main focus will be on text in the People’s Daily, the largest newspaper in China and the official newspaper of the Chinese Communist Party.

Commonsense reasoning refers to the ability of capitalising on commonly used knowledge by most people, and making decisions accordingly. This process usually involves combining multiple commonsense facts and beliefs to draw a conclusion or judgement. While human trivially performs such reasoning, current Artificial Intelligence models fail, mostly due to challenges of acquiring relevant knowledge and forming logical connections between them. This project aims to develop and evaluate machine learning models for commonsense reasoning, with question answering as the key application. 

Developing quality AI tools for legal texts is the focus of enormous industry, government and
scholarly attention. The potential benefits include greater efficiency, transparency and access to justice.
Moving beyond the hype requires novel transdisciplinary effort to combine IT and Law expertise.
This project engages this challenge by developing a semi-structured knowledge base (KB) and
reasoners for statutes and cases. The project will also construct corresponding training and evaluation
datasets.