Staff profile
Overview
https://apps.dur.ac.uk/biography/image/1480
Professor Ian Vernon
Professor, Statistics
Affiliation | Telephone |
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Professor, Statistics in the Department of Mathematical Sciences | +44 (0) 191 33 43068 |
Research interests
- Bayesian Statistics
- Bayes Linear Methods
- Uncertainty Analysis of Computer Models of Complex Physical Systems
- Galaxy Formation Simulations
- Systems Biology Models
- Epidemiology HIV Models
- Geology models of oil reservoirs
Esteem Indicators
- 2011: Awarded Michell Prize for Best Applied Bayesian Article Worldwide 2010.: The Michell Prize is awarded for the best applied Bayesian Statistics article worldwide, and is considered to be the top research prize for Bayesian Statistics. It is awarded jointly by the Section on Bayesian Statistical Science (SBSS) of the America Statistical Association, the International Society for Bayesian Analysis (ISBA), and the Mitchell Prize Founders' Committee. We were awarded this prize for the invited discussion paper, for which I was first author:
Vernon, I., Goldstein, M., and Bower, R. G. (2010), “Galaxy Formation: a Bayesian Uncertainty Analysis,” Bayesian Analysis 5(4), 619–846, with Discussion.
Publications
Chapter in book
Conference Paper
- Carter, J., & Vernon, I. (2022, December). Gaussian Process Models for Well Placement Optimisation. Presented at ECMOR 2022, The Hague, Netherlands
- Bordas, R., Heritage, J., Javed, M., Peacock, G., Taha, T., Ward, P., Vernon, I., & Hammersley, R. (2020, September). A Bayesian Optimisation Workflow for Field Development Planning Under Geological Uncertainty. Presented at ECMOR XVII
- Formentin, H. N., Vernon, I., Goldstein, M., Caiado, C., Avansi, G., & Schiozer, D. (2020, September). Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques. Presented at ECMOR XVII
- Owen, J., Vernon, I., & Hammersley, R. (2020, September). A Bayesian Statistical Approach to Decision Support for TNO OLYMPUS Well Control Optimisation under Uncertainty. Presented at ECMOR XVII
- Nandi Formentin, H., Vernon, I., Avansi, G. D., Caiado, C., Maschio, C., Goldstein, M., & Schiozer, D. J. (2019, June). Systematic uncertainty reduction for petroleum reservoirs combining reservoir simulation and Bayesian emulation techniques. Presented at SPE Europec featured at 81st EAGE Annual Conference 2019, London
- Ferreira, C., Avansi, G., Vernon, I., Schiozer, D., & Goldstein, M. (2018, September). Evaluation of Regions of Influence for Dimensionality Reduction in Emulation of Production Data. Presented at ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery, Barcenola, Spain
- Ferreira, C., Davolio, A., Schiozer, D., Vernon, I., & Goldstein, M. (2015, December). Use of Emulator and Canonical Correlation to Incorporate 4D Seismic Data in the Reduction of Uncertainty Process. Presented at EUROPEC 2015, Madrid, Spain
- Ferreira, C., Vernon, I., Schiozer, D., & Goldstein, M. (2014, December). Use of Emulator Methodology for Uncertainty Reduction Quantification. Presented at SPE Latin America and Caribbean Petroleum Engineering Conference, Maracaibo, Venezuela
- Vernon, I. R., & Goldstein, M. (2009, July). Bayes Linear Analysis of Imprecision in Computer Models, with Application to Understanding Galaxy Formation. Presented at Sixth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'09), Durham University
Journal Article
- McCreesh, N., Andrianakis, I., Nsubuga, R., Strong, M., Vernon, I., McKinley, T., Oakley, J., Goldstein, M., Hayes, R., & White, R. (in press). Costs and effects of changes to ART eligibility criteria in Uganda. PLoS ONE,
- Jackson, S. E., Vernon, I., Liu, J., & Lindsey, K. Bayesian uncertainty analysis establishes the link between the parameter space of a complex model of hormonal crosstalk in Arabidopsis root development and experimental measurements [preprint]. Manuscript submitted for publication
- Ferreira, C., Vernon, I., Caiado, C., Formentin, H., Avansi, G., Goldstein, M., & Schiozer, D. (online). Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis. SPE Journal, OTC-29801. https://doi.org/10.4043/29801-ms
- Iskauskas, A., Vernon, I., Goldstein, M., Scarponi, D., McKinley, T. J., White, R. G., & McCreesh, N. (2024). Emulation and History Matching using the hmer Package. Journal of Statistical Software, 109(10), 1–48. https://doi.org/10.18637/jss.v109.i10
- Vernon, I., & Gosling, J. (2023). A Bayesian Computer Model Analysis of Robust Bayesian Analyses. Bayesian Analysis, 18(4), 1367-1399. https://doi.org/10.1214/22-ba1340
- Kugel, R., Schaye, J., Schaller, M., Helly, J. C., Braspenning, J., Elbers, W., Frenk, C. S., McCarthy, I. G., Kwan, J., Salcido, J., van Daalen, M. P., Vandenbroucke, B., Bahé, Y. M., Borrow, J., Chaikin, E., Huško, F., Jenkins, A., Lacey, C. G., Nobels, F. S. J., & Vernon, I. (2023). FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning. Monthly Notices of the Royal Astronomical Society, 526(4), 6103-6127. https://doi.org/10.1093/mnras/stad2540
- Kondo, Y., Achouri, N. L., Falou, H. A., Atar, L., Aumann, T., Baba, H., Boretzky, K., Caesar, C., Calvet, D., Chae, H., Chiga, N., Corsi, A., Delaunay, F., Delbart, A., Deshayes, Q., Dombrádi, Z., Douma, C. A., Ekström, A., Elekes, Z., Forssén, C., …Yoshida, S. (2023). First observation of 28O. Nature, 620(7976), 965-970. https://doi.org/10.1038/s41586-023-06352-6
- Scarponi, D., Iskauskas, A., Clark, R. A., Vernon, I., McKinley, T. J., Goldstein, M., Mukandavire, C., Deol, A., Weerasuriya, C., Bakker, R., White, R. G., & McCreesh, N. (2023). Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmer. Epidemics, 43, Article 100678. https://doi.org/10.1016/j.epidem.2023.100678
- Jackson, S. E., & Vernon, I. (2023). Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimension. Bayesian Analysis, 18(1), 165-191. https://doi.org/10.1214/22-ba1304
- Vernon, I., Owen, J., Aylett-Bullock, J., Cuestra-Lazaro, C., Frawley, J., Quera-Bofarull, A., Sedgewick, A., Shi, D., Truong, H., Turner, M., Walker, J., Caulfield, T., Fong, K., & Krauss, F. (2022). Bayesian Emulation and History Matching of JUNE. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380(2233), Article 20220039. https://doi.org/10.1098/rsta.2022.0039
- Hu, B., Jaing, W., Miyagi, T., Sun, Z., Ekström, A., Forssén, C., Hagen, G., Holt, J. D., Papenbrock, T., Stroberg, S. R., & Vernon, I. (2022). Ab initio predictions link the neutron skin of 208Pb to nuclear forces. Nature Physics, 18(10), 1196-1200. https://doi.org/10.1038/s41567-022-01715-8
- Dunne, M., Mohammadi, H., Challenor, P., Borgo, R., Porphyre, T., Vernon, I., Firat, E. E., Turkay, C., Torsney-Weir, T., Goldstein, M., Reeve, R., Fang, H., & Swallow, B. (2022). Complex model calibration through emulation, a worked example for a stochastic epidemic model. Epidemics, 39, Article 100574. https://doi.org/10.1016/j.epidem.2022.100574
- Swallow, B., Birrell, P., Blake, J., Burgman, M., Challenor, P., Coffeng, L. E., Dawid, P., De Angelis, D., Goldstein, M., Hemming, V., Marion, G., McKinley, T. J., Overton, C. E., Panovska-Griffiths, J., Pellis, L., Probert, W., Shea, K., Villela, D., & Vernon, I. (2022). Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38, https://doi.org/10.1016/j.epidem.2022.100547
- Aylett-Bullock, J., Cuesta-Lazaro, C., Quera-Bofarull, A., Icaza-Lizaola, M., Sedgewick, A., Truong, H., Curran, A., Elliott, E., Caulfield, T., Fong, K., Vernon, I., Williams, J., Bower, R., & Krauss, F. (2021). JUNE: open-source individual-based epidemiology simulation. Royal Society Open Science, 8(7), https://doi.org/10.1098/rsos.210506
- Jackson, S., Vernon, I., Liu, J., & Lindsey, K. (2020). Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching. Statistical Applications in Genetics and Molecular Biology, 19(2), Article 20180053. https://doi.org/10.1515/sagmb-2018-0053
- Formentin, H. N., Almeida, F. L. R., Avansi, G. D., Maschio, C., Schiozer, D. J., Caiado, C., Vernon, I., & Goldstein, M. (2019). Gaining more understanding about reservoir behavior through assimilation of breakthrough time and productivity deviation in the history matching process. Journal of Petroleum Science and Engineering, 173, 1080-1096. https://doi.org/10.1016/j.petrol.2018.10.045
- Vernon, I., Jackson, S., & Cumming, J. (2019). Known Boundary Emulation of Complex Computer Models. SIAM/ASA Journal on Uncertainty Quantification, 7(3), 838-876. https://doi.org/10.1137/18m1164457
- Moreno, R., Avansi, G., Schiozer, D., Vernon, I., Goldstein, M., & Caiado, C. (2018). Emulation of reservoir production forecast considering variation in petrophysical properties. Journal of Petroleum Science and Engineering, 165, 711-725. https://doi.org/10.1016/j.petrol.2018.02.056
- McCreesh, N., Andrianakis, I., Nsubuga, R. N., Strong, M., Vernon, I., McKinley, T. J., Oakley, J. E., Goldstein, M., Hayes, R., & White, R. G. (2018). Choice of time horizon critical in estimating costs and effects of changes to HIV programmes. PLoS ONE, 13(5), Article e0196480. https://doi.org/10.1371/journal.pone.0196480
- McKinley, T., Vernon, I., Andrianakis, I., McCreesh, N., Oakley, J., Nsubuga, R., Goldstein, M., & White, R. (2018). Approximate Bayesian Computation and simulation-based inference for complex stochastic epidemic models. Statistical Science, 33(1), 4-18. https://doi.org/10.1214/17-sts618
- Vernon, I., Liu, J., Goldstein, M., Rowe, J., Topping, J., & Lindsey, K. (2018). Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions. BMC systems biology, 12, Article 1. https://doi.org/10.1186/s12918-017-0484-3
- Vernon, I. (2018). Uncertainty Analysis for Heavy Simulations of Galaxy Formation
- McCreesh, N., Andrianakis, I., Nsubuga, R., Strong, M., Vernon, I., McKinley, T., Oakley, J., Goldstein, M., Hayes, R., & White, R. (2017). Improving ART programme retention and viral suppression are key to maximising impact of treatment as prevention – a modelling study. BMC Infectious Diseases, 17(1), Article 557. https://doi.org/10.1186/s12879-017-2664-6
- Andrianakis, I., Vernon, I., McCreesh, N., McKinley, T., Oakley, J., Nsubuga, R., Goldstein, M., & White, R. (2017). History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation. Journal of the Royal Statistical Society: Series C, 66(4), 717-740. https://doi.org/10.1111/rssc.12198
- Andrianakis, I., McCreesh, N., Vernon, I., McKinley, T., Oakley, J., Nsubuga, R., Goldstein, M., & White, R. (2017). Efficient History Matching of a High Dimensional Individual-Based HIV Transmission Model. SIAM/ASA Journal on Uncertainty Quantification, 5(1), 694-719. https://doi.org/10.1137/16m1093008
- McCreesh, N., Andrianakis, I., Nsubuga, R., Strong, M., Vernon, I., McKinley, T., Oakley, J., Goldstein, M., Hayes, R., & White, R. (2017). Universal test, treat, and keep: improving ART retention is key in cost-effective HIV control in Uganda. BMC Infectious Diseases, 17, Article 322. https://doi.org/10.1186/s12879-017-2420-y
- Rodrigues, L. F. S., Vernon, I., & Bower, R. G. (2017). Constraints on galaxy formation models from the galaxy stellar mass function and its evolution. Monthly Notices of the Royal Astronomical Society, 466(2), 2418-2435. https://doi.org/10.1093/mnras/stw3269
- Andrianakis, I., Vernon, I., McCreesh, N., McKinley, T., Oakley, J., Nsubuga, R., Goldstein, M., & White, R. (2015). Bayesian history matching of complex infectious disease models using emulation: A tutorial and a case study on HIV in Uganda. PLoS Computational Biology, 11(1), Article e1003968. https://doi.org/10.1371/journal.pcbi.1003968
- Vernon, I., Goldstein, M., & Bower, R. (2014). Galaxy Formation: Bayesian History Matching for the Observable Universe. Statistical Science, 29(1), 81-90. https://doi.org/10.1214/12-sts412
- Vernon, I., Goldstein, M., & Bower, R. G. (2010). Rejoinder - Galaxy Formation: a Bayesian Uncertainty Analysis. Bayesian Analysis, 05(04), 697-708. https://doi.org/10.1214/10-ba524rej
- Vernon, I., Goldstein, M., & Bower, R. G. (2010). Galaxy Formation: a Bayesian Uncertainty Analysis. Bayesian Analysis, 05(04), 619-670. https://doi.org/10.1214/10-ba524
- Bower, R., Vernon, I., Goldstein, M., Benson, A., Lacey, C., Baugh, C., Cole, S., & Frenk, C. (2010). The Parameter Space of Galaxy Formation. Monthly Notices of the Royal Astronomical Society, 407(4), 2017-2045. https://doi.org/10.1111/j.1365-2966.2010.16991.x
- Vernon, I. R., & Jennings, D. (2005). Graviton Emission into Non-Z_2 Symmetric Brane World Spacetimes. Journal of Cosmology and Astroparticle Physics, 07, https://doi.org/10.1088/1475-7516/2005/07/011
- Jennings, D., Vernon, I. R., Davis, A.-C., & van de Bruck, C. (2005). Bulk black holes radiating in non-Z_2 brane-world spacetimes. Journal of Cosmology and Astroparticle Physics, 2005(04), Article 013. https://doi.org/10.1088/1475-7516/2005/04/013
- Davis, A.-C., Rhodes, C., & Vernon, I. R. (2001). Branes on the Horizon. Journal of High Energy Physics, 11, https://doi.org/10.1088/1126-6708/2001/11/015
- Davis, A.-C., Vernon, I., Davis, S. C., & Perkins, W. B. (2001). Brane World Cosmology Without the Z_2 Symmetry. Physics Letters B, 504(3), 254-261. https://doi.org/10.1016/s0370-2693%2801%2900291-x
- Davis, S. C., Perkins, W. B., Davis, A.-C., & Vernon, I. R. (2001). Cosmological phase transitions in a brane world. Physical Review D, Particles and fields, 63(8), Article 083518. https://doi.org/10.1103/physrevd.63.083518
Report
- Vernon, I., Seheult, A., & Goldstein, M. (2010). Modular Dynamic Emulation and Internal Model Discrepancy for a Rainfall Runoff Model. MUCM
- Vernon, I. R., & Goldstein, M. (2010). A Bayes Linear Approach to Systems Biology. MUCM
- House, L., Goldstein, M., & Vernon, I. (2009). Exchangeable Computer Models. MUCM
- Vernon, I., Goldstein, M., & Bower, R. G. (2009). Galaxy Formation: a Bayesian Uncertainty Analysis. MUCM
Supervision students
Zhaocheng Li
1S