Dr Oludare Ariyo
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Email
oludare.ariyo@essex.ac.uk -
Telephone
+44 (0) 1206 872851
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Location
3A.524, Colchester Campus
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Academic support hours
Open door policy
Profile
Biography
Oludare Ariyo is a lecturer at the School of Mathematics, Statistics, and Actuarial Science at the University of Essex. He holds a PhD in Biostatistics from KU Leuven Belgium, where he worked on Bayesian model selection for longitudinal random-effects models. Before joining the University of Essex, Oludare worked as a Lecturer in Statistics at the Federal University of Agriculture in Abeokuta from 2013 to 2022. He has also worked as a Data Analyst at the Crop Utilization Units at the International Institutes of Tropical Agriculture Ibadan and as a Senior Statistician at the National Horticultural Research Institutes (NIHORT), Ibadan, Nigeria. Oludare's research interests include developing statistical methodology in health, environment, agriculture, and social research domains. He is particularly interested in Biostatistics and Data Science domains, with extensive practice in high-dimensional data analyses, modelling of longitudinal data with missing data/survival analysis, and mixed models/random-effects models/multilevel models. Currently, he is working on a Bayesian model for structured covariance that the Royal Society funds. He is open to PhD supervision. Please get in touch with him if you have an appropriate background in statistics, especially in Bayesian statistics, Biostatistics, Mixed-model and machine learning
Qualifications
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PhD (Biostatistics) KU Leuven, (2020)
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M.Sc (Statistics) Federal University of Agriculture, (2010)
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B.Sc (Mathematical Sciences) Federal University of Agriculture, (2005)
Appointments
University of Essex
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Lecturer, Mathematical Sciences, University of Essex (1/10/2022 - present)
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Lecturer, Statistics, Federal University of Agriculture (26/12/2013 - 30/9/2022)
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Research Associate, Department of Public Health and Primary Care, Katholieke Universiteit Leuven (1/2/2016 - 30/6/2020)
Research and professional activities
Research interests
Biostatistics
Bayesian computational statistics
Joint modelling for longitudinal and survival analysis.
Multivariate Analysis
Mixed-Effect model
High-Dimensional data
Models for multivariate repeated measures
Conferences and presentations
The 44th Annual Conference of the International Society for Clinical Biostatistics (ISCB)
28/8/2023
Prior distributions for structured covariance matrices
Invited presentation, 43th International Society for Clinical Biostatistics, Newcastle UK, 17/8/2022
Prior distributions for structured covariance matrices
Invited presentation, 86th International Meetings of the Psychometric Society, USA, United States, 20/7/2021
Bayesian model selection for generalized linear mixed mode
Invited presentation, 40th Annual Conference of the International Society for Clinical Biostatistics, Belgium, 15/7/2019
Comparing skew-normal linear mixed models with nonignorable dropout via observed deviance information criterion
Invited presentation, 61st World Statistics Congres, Marrakech, Morroco, 20/7/2017
Model selection for the skew-normal linear mixed models with covariate measurements errors
Invited presentation, 6th IBS Channel Network Conference, Hasselt, Belgium, 12/7/2017
Bayesian inference for skew-normal linear mixed models with covariates measurements errors
38th Annual Conference of the International Society for Clinical Biostatistics, Vigo Spain, 10/7/2017
Teaching and supervision
Current teaching responsibilities
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Applied Statistics (MA321)
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Applied Regression and Experimental Data Analysis (MA717)
Publications
Journal articles (9)
Ariyo, O., Olobatuyi, K. and Baghfalaki, T., (2025). A Bayesian Joint Bent-cable Model for Longitudinal Measurements and Survival Time with Heterogeneous Random-effects Distributions. Journal of Biopharmaceutical Statistics, 1-14
Olobatuyi, K., Parker, MRP. and Ariyo, O., (2023). Cluster weighted model based on TSNE algorithm for high-dimensional data. International Journal of Data Science and Analytics. 17 (3), 261-273
Merkle, EC., Ariyo, O., Winter, SD. and Garnier-Villarreal, M., (2023). Opaque prior distributions in Bayesian latent variable models. Methodology. 19 (3), 228-255
Ariyo, E., Amurtiya, M., Lydia, OY., Ariyo, O., Ololade, O., Taiwo, AP., Olukemi, LA. and Ogunniyi, D., (2022). Socio-demographic determinants of children home learning experiences during COVID 19 school closure.. International Journal of Educational Research Open. 3, 100111-100111
Ariyo, O., Lesaffre, E., Verbeke, G. and Quintero, A., (2022). Bayesian Model Selection for Longitudinal Count Data. Sankhya B. 84 (2), 516-547
Ariyo, O., Lesaffre, E., Verbeke, G., Huisman, M., Heymans, M. and Twisk, J., (2022). Bayesian model selection for multilevel mediation models. Statistica Neerlandica. 76 (2), 219-235
Ariyo, O., Lesaffre, E., Verbeke, G. and Quintero, A., (2022). Model selection for Bayesian linear mixed models with longitudinal data: Sensitivity to the choice of priors. Communications in Statistics: Simulation and Computation. 51 (4), 1591-1615
Ariyo, OS. and Adeleke, MA., (2022). Simultaneous Bayesian modelling of skew-normal longitudinal measurements with non-ignorable dropout. Computational Statistics. 37 (1), 303-325
Ariyo, O., Quintero, A., Muñoz, J., Verbeke, G. and Lesaffre, E., (2020). Bayesian model selection in linear mixed models for longitudinal data. Journal of Applied Statistics. 47 (5), 890-913
Reports and Papers (1)
Ariyo, O., Merkle, E., Winter, S. and Garnier-Villarreal, M., Opaque prior distributions in Bayesian latent variable models.
Grants and funding
2023
Bayesian modelling for structured covariance matrices
The Royal Society
Contact
Academic support hours:
Open door policy
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