Meriel Huggard

Individualised project in Wireless networking, Machine Learning, Artificial Intelligence, Quantum Computing (and associated application domains)

Meriel Huggard (email | all projects)

I am happy to supervise a project in all the areas of computer networking that I am interested in — wireless networking, Machine Learning, Artificial Intelligence and in their application to a wide range of real world settings (healthcare, IoT, structural health monitoring). I am particularly interested in exploring some aspects of quantum computing; for … Read more

Federated Learning for Imbalanced Datasets

Meriel Huggard (email | all projects)

The performance of artificial intelligence based learning models is often initially assessed using well established benchmark datasets. However, satisfactory performance on these datasets does not guarantee similar performance in real-world settings where the data may be significantly more imbalanced.  For example, in a medical dataset a positive diagnosis may be a relatively rare event and … Read more

Using AI to develop a Concept Inventories for CS Education

Meriel Huggard (email | all projects)

Concept inventories are research-based multiple-choice tests that are used in educational settings to measure a student’s knowledge of a set of concepts while also capturing conceptions and misconceptions they may have about the topic under consideration. They provide useful information for students, lecturers and educational researchers. For example, they can provide lecturers with a measure … Read more

Personalised Federated Learning

Meriel Huggard (email | all projects)

Federated learning is used in distributed collaborative networks where multiple clients coordinate to train AI models without the need to share raw data. This is advantageous in a number of settings; for example; in health care where there are privacy/ethical issues associated with sharing data across multiple sites and in IoT networks where the sharing … Read more

Privacy and Trust in Federated learning

Meriel Huggard (email | all projects)

In the world of big data and artificial intelligence, federated learning is a very attractive way of enabling data sharing in a privacy preserving manner. Clients in a federated learning network never access data from other clients directly and they model parameters they receive are formed from data aggregates.  However, under certain conditions the models … Read more