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Trinity Centre for Ageing and Intellectual Disability

  • Dr Caitríona Ryan

    • Dr Caitríona Ryan

    Lead Statistician

    Qualifications: PhD (Statistics), MSc (Statistics), BSc (Mathematical Science) from University College Dublin

    Research interests: Statistical modelling of longitudinal data, Anomaly detection, Social network analysis, Statistical design of experiments, Model based clustering

    Email: ryanc86@tcd.ie

    Caitríona is the lead statistician at IDS-TILDA. She completed her taught MSc in statistics and PhD in Bayesian social network analysis at University College Dublin (UCD) in 2014. She supports statistical analysis across all research topics in IDS-TILDA and has a particular interest in developing longitudinal data analysis skills across the team.

    She has previously held appointments at Maynooth University, UCD, University of Limerick (UL) and Queensland University of Technology in Brisbane. Research outputs include peer-reviewed high-level publications in social network analysis and experimental design and open source software for analyses of clustering of networks and anomaly detention in time series analysis. Teaching experience includes lecturing at UL and UCD, design and online facilitation of training courses as well as mentoring, assisting and collaborating with PhD and MSc students.

  • Publications:

    • “Using in situ process monitoring data to identify defective layers in Ti64AI4V additively manufactured porous biomaterials”. DS Egan, CM Ryan, A Parnell, DP Dowling (2021): Journal of Manufacturing Process, 64(1248-1254)

    • “Development of a standalone In-situ Monitoring System for Defect Detection in the Direct Metal Laser Sintering Process”. P Quinn, S O'Halloran , CM Ryan, A Parnell, J Lawlor, R Raghavendra (Solid Freeform Symposium 2019)

    • “Bayesian Model Selection for the Latent Position Cluster Model for Social Networks”. CM Ryan, J Wyse, & N Friel, (2017): Network Science 5(1)

    • “An Optimal Bayesian Experimental Design for Models with Intractable Likelihoods Using Indirect Inference Applied to Biological Process Models”. CM Ryan, CC Drovandi, & AN Pettitt, (2016): Bayesian Analysis

    Software:

    • J Wyse,& CM Ryan (2017). collpcm: Collapsed Latent position cluster model for social networks. R package version 1.0.https://CRAN.R-project.org/package=collpcm

    • CM Ryan, A Parnell, C Mahoney (2019). anomalystreamr: Real-time statistically principled anomaly detection in time series data implemented in R. https://github.com/trionaryan/anomalystreamr