• Room 0G.009 - Old Physics

    United Kingdom

20002019

Research output per year

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Personal profile

Interests

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.

Particulars

Chair of the Statistics and Operational Research Examination Board.

Research Statement

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

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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Projects

Research Output

Analysing the Performance of a Real-Time Healthcare 4.0 System using Shared Frailty Time to Event Models

Marshall, A. H. & Novakovic, A., 05 Aug 2019, 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS). IEEE , p. 622-627 ( 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
File
  • A state-of-the-art review of Network level bridge management systems and proposal of new approach for predictive maintenance

    Lydon, D., Lydon, M., Taylor, S., Soundararajan, P. & Marshall, A. H., 05 Sep 2019, Irish Transport Research Network 05/09/2019 → 06/09/2019 Belfast, United Kingdom.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • Cattle movements in Northern Ireland form a robust network: implications for disease management

    Brown, E., Marshall, A. H., Mitchell, H. J. & Bryne, A. W., 01 Oct 2019, In : Preventive veterinary medicine. 170, 9 p., 104740.

    Research output: Contribution to journalArticle

  • 1 Citation (Scopus)

    A Bayesian network based learning system for modelling faults in large-scale manufacturing

    Carbery, C. M., Woods, R. & Marshall, A. H., 30 Apr 2018, Proceedings - 2018 IEEE International Conference on Industrial Technology, ICIT 2018. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-February. p. 1357-1362 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • 3 Citations (Scopus)
    350 Downloads (Pure)

    Prizes

    International Statistics Institute invited member

    Adele Marshall (Recipient), 2011

    Prize: Election to learned society

    Activities

    Statistics Course for School Teachers: Examine how to teach statistical content through the interrogation of data.

    Adele Marshall (Organiser)
    30 Mar 2018

    Activity: Participating in or organising an event typesParticipation in workshop, seminar, course

    A study of cattle movements in Northern Ireland for 2005:2015 using social network analysis

    Hannah Mitchell (Advisor), A.H. Marshall (Advisor), Emma Brown (Presenter), Andrew Bryne (Advisor)
    2018

    Activity: Talk or presentation typesOral presentation

    Western University

    Adele Marshall (Visiting researcher)
    Apr 2018

    Activity: Visiting an external institution typesVisiting an external academic institution

    IEEE 31st International Symposium on Computer Based Medical Systems

    Adele Marshall (Conference committee co-chair)
    18 Jun 201821 Jun 2018

    Activity: Participating in or organising an event typesParticipation in conference

    Northern Ireland Audit Office Conference - Cultivating Curiousity

    Adele Marshall (Invited speaker)
    16 Mar 2018

    Activity: Talk or presentation typesInvited or keynote talk at national or international conference

    Press / Media

    ABC Radio Interview

    Adele Marshall

    19/05/2016

    1 Media contribution

    Press/Media: Expert Comment

    Thesis

    Longitudinal Joint Modelling Utilising the Coxian Phase-type Distribution

    Author: Donnelly, C., 2019

    Supervisor: Marshall, A. (Supervisor) & McFetridge, L. (Supervisor)

    Student thesis: Doctoral ThesisDoctor of Philosophy

    File