Lisa McFetridge is the Thematic Lead for Statistics and Data Analytics in the School of Mathematics and Physics at Queen’s University Belfast. Her research develops novel statistical techniques for the modelling, analysis, forecasting and visualisation of complex real-world data.

Predominantly, her work concentrates on the joint analysis of longitudinal and survival data, discrete choice modelling and the use of advanced machine learning techniques for disease classification, typically for the prediction of rare events. Her current research direction has an emphasis on anomaly detection, multivariate analysis of multiple input streams, Bayesian inference and handling intensive longitudinal data, such as that typically collected from electronic sensors.

As such, her research is highly collaborative in nature, frequently linking with local companies to embed cutting-edge statistical techniques into their processes through Knowledge Transfer Partnerships. Due to the synergy between patients' repeated measurements and the time until an event of interest, her work naturally lends itself to a wide variety of medical applications, allowing a deeper understanding of patient-specific reaction to treatments and thus is a key tool in the establishment of precision medicine, providing a personalised prognosis for patients.

Lisa is a Council member and Trustee for the Royal Statistical Society, member of the EPSRC Mathematical Sciences Strategic Advisory Team, Education Officer for the Irish Statistical Association, past Programme Chair for the International Conference of the Royal Statistical Society (2018-19) and member of the RSS Conferences and Events Programme Board.