Dr Vinny Davies

  • Research Associate (School of Computing Science)
  • Honorary Research Fellow (Statistics)

Biography

Dr Davies is currently a Research Associate in the School of Computing Science and a member of the Inference, Dynamics and Interaction group. He did his undergraduate in Mathematics and Masters in Statistics at Lancaster University, before moving to the School of Mathematics and Statistics at the University of Glasgow to do his Ph.D with Prof Dirk Husmeier, where his Ph.D. focused on variable selection models for selecting antigenic sites in virus evolution. He then worked on methods for parameter in mathematical models of the heart, before moving to the University of Leeds to become a Biostatistician. He then returned to the University in Septemeber 2018 to become a Research Associate working as part of the EPSRC Closed-Loop Data Science project. As part of this project, he looks at developing new methods for closed loop mass spectrometry measurement and analysis of metabolomics.


Research datasets

Jump to: 2019
Number of items: 1.

2019

Wandy, J., Davies, V. , van der Hooft, J., Weidt, S., Daly, R. and Rogers, S. (2019) In-silico Optimisation of Mass Spectrometry Fragmentation Strategies in Metabolomics. [Data Collection]

This list was generated on Tue Sep 17 20:14:06 2019 BST.

Publications

List by: Type | Date

Jump to: 2019 | 2017 | 2016 | 2014 | 2013
Number of items: 11.

2019

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A., Macdonald, B., Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Theoretical and Applied Nanoscience and Nanotechnology (ICSTA'19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi:10.11159/icsta19.29)

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), (Accepted for Publication)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi:10.1098/rsif.2019.0114) (PMID:31266415)

Davies, V. , Harvey, W. T., Reeve, R. and Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. Journal of the Royal Statistical Society: Series C (Applied Statistics), (doi:10.1111/rssc.12338) (Early Online Publication)

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a computational model of the left-ventricle using emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), (Accepted for Publication)

2017

Davies, V. , Reeve, R. , Harvey, W. T., Maree, F. F. and Husmeier, D. (2017) A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution. Computational Statistics, 32(3), pp. 803-843. (doi:10.1007/s00180-017-0730-6)

2016

Davies, V. , Reeve, R. , Harvey, W. T. and Husmeier, D. (2016) Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability. In: Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers. Series: Lecture Notes in Computer Science (9874). Springer, pp. 14-27. ISBN 9783319443317 (doi:10.1007/978-3-319-44332-4_2)

2014

Davies, V. , Reeve, R. , Harvey, W., Maree, F. and Husmeier, D. (2014) Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus. Proceedings of Machine Learning Research, 33, pp. 149-158.

Davies, V. and Husmeier, D. (2014) Modelling transcriptional regulation with Gaussian processes. In: Valente, A. X.C.N., Sarkar, A. and Gao, Y. (eds.) Recent Advances in Systems Biology Research. Nova Science Publishers: New York, pp. 157-184. ISBN 9781629487366

2013

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer.

Davies, V. and Husmeier, D. (2013) Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 559-562. ISBN 9788896251492

This list was generated on Tue Sep 17 12:14:54 2019 BST.
Number of items: 11.

Articles

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), (Accepted for Publication)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi:10.1098/rsif.2019.0114) (PMID:31266415)

Davies, V. , Harvey, W. T., Reeve, R. and Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. Journal of the Royal Statistical Society: Series C (Applied Statistics), (doi:10.1111/rssc.12338) (Early Online Publication)

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a computational model of the left-ventricle using emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), (Accepted for Publication)

Davies, V. , Reeve, R. , Harvey, W. T., Maree, F. F. and Husmeier, D. (2017) A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution. Computational Statistics, 32(3), pp. 803-843. (doi:10.1007/s00180-017-0730-6)

Davies, V. , Reeve, R. , Harvey, W., Maree, F. and Husmeier, D. (2014) Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus. Proceedings of Machine Learning Research, 33, pp. 149-158.

Book Sections

Davies, V. , Reeve, R. , Harvey, W. T. and Husmeier, D. (2016) Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability. In: Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers. Series: Lecture Notes in Computer Science (9874). Springer, pp. 14-27. ISBN 9783319443317 (doi:10.1007/978-3-319-44332-4_2)

Davies, V. and Husmeier, D. (2014) Modelling transcriptional regulation with Gaussian processes. In: Valente, A. X.C.N., Sarkar, A. and Gao, Y. (eds.) Recent Advances in Systems Biology Research. Nova Science Publishers: New York, pp. 157-184. ISBN 9781629487366

Davies, V. and Husmeier, D. (2013) Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 559-562. ISBN 9788896251492

Research Reports or Papers

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer.

Conference Proceedings

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A., Macdonald, B., Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Theoretical and Applied Nanoscience and Nanotechnology (ICSTA'19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi:10.11159/icsta19.29)

This list was generated on Tue Sep 17 12:14:54 2019 BST.