Projects per year
Research interests include Survival Analysis, Bayesian Modelling, Data Mining, Markov Modelling and Stochastic Models. Research applications range from a strong foundation in healthcare research and medical Statistics and Operational Research to infrastructure modelling and flow modelling. Research funding from both national and international sources continues to underpin this research effort.
Chair of the Statistics and Operational Research Examination Board.
The main area of my research has specialised in Coxian phase-type distributions. Since commencing work in this field in 1997, the area which had barely any research is gradually gaining momentum with more and more researchers wishing to explore the models for alternative use, further research and development and application.
Alongside this, the work I've conducted and supervised through CenSSOR has led to Queen's being seen as experts in this field. In the last 2 years, major developments in the coding has resulted in the various models now becoming much more accessible to researchers in other domains. Future research in this field is very promising.
The original research focused on healthcare of the elderly. The UK Health Reform in 2010 and growing needs for all countries to plan and manage elderly healthcare and its associated costs makes the research extremely topical and relevant to have impact on society.
One mechanism for making this possible is the Cunberland Initiative Group of which I am a founding member. We are in the process of preparing a multi-million bid for submission to the Technology Strategy Board (TSB) grant which would be supported by other grant bodies such as EPSRC, Department of Health, and NIHR. We have also started consultancy work with some of the regional health groups.
Teaching interests involve all areas of Statistics. In particular, I am involved with the development of new modules and course pathways. In 2005, the pathway for Mathematics, Statistics & Operational Research was introduced.
More recently in 2017, I developed the new MSc Data Analytics course as a new Faculty initiative in partnership with industry. The course is now open for applications with the first intake of students starting in September 2017. As Programme Director of the course, I have outlined its priorities to deliver highly skilled experts in data analytics who will be trained in both the computational and statistical aspects of the subject area. The course has been developed to meet the growing demands for data analytics and data science experts in industry providing modules such as Fundamentals in Data Analytics, Progamming and Database Fundamentals, Data Mining, Machine Learning, Frontiers in Analytics (which includes Behavioural Analytics and Visual Analytics) and Analytics in Action where we run our own Analytathons.
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Kee, F., Cantwell, M., Clarke, M., Coleman, H., Connolly, P., Cupples, M., Donnelly, M., French, D., Hutchinson, G., Kouvonen, A., Longo, A., Marshall, A., McCann, J., McKinley, M., Moore, M., Murray, L., O'Reilly, D., Patterson, C., Tully, M., Woodside, J. & Young, I.
01/08/2012 → …
Novakovic, A., Marshall, A. H. & McGregor, C., 06 Aug 2021, Advances in Computer Vision and Computational Biology. Springer Nature Switzerland AG, (Transactions on Computational Science and Computational Intelligence).
Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
Lydon, M., Lydon, D., Stevens, N-A., Taylor, S., Early, J. & Marshall, A. H., 01 Aug 2021, (Accepted) In: Journal of Infrastructure Preservation and Resilience.
Research output: Contribution to journal › Article › peer-review
Lydon, M., Lydon, D., Stevens, N-A., Taylor, S., Early, J. & Marshall, A. H., 13 Sep 2021, In: Journal of Infrastructure Preservation and Resilience.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile1 Downloads (Pure)
Academic Students’ Progress Indicators and Gender Gaps Based on Survival Analysis and Data Mining FrameworksMarshall, A. H., Zenga, M. & Kalamatianou, A., 01 Oct 2020, In: Social Indicators Research. 151, 3, p. 1097-1128
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile6 Downloads (Pure)
A joint likelihood approach to the analysis of length of stay data utilising the continuous-time hidden Markov model and Coxian phase-type distributionMitchell, H. J., Marshall, A. H. & Zenga, M., 08 Aug 2020, (Early online date) In: Journal of the Operational Research Society.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile
Adele Marshall (Invited speaker)16 Mar 2018
Activity: Talk or presentation types › Invited or keynote talk at national or international conference
Activity: Talk or presentation types › Oral presentation