Meriel Huggard

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

Vehicles are equipped with ever increasingly advanced communication and sensing resources, giving rise to the need for effective mechanisms to utilise and leverage the large amounts of data they gather.  For example, this data could be used to predict traffic flow and to monitor driver behaviour. There are many different, distributed machine learning techniques that … Read more

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