Professor Surajit Ray

  • Professor (Statistics)

telephone: 01413306238
email: Surajit.Ray@glasgow.ac.uk

School of Mathematics, & Statistics, Mathematics Building

Import to contacts

ORCID iDhttps://orcid.org/0000-0003-3965-8136

Biography

Personal Webpage: https://surajitray.org/

Research interests

My research interests are in the area of model selection, the theory and geometry of mixture models and functional data analysis. I am especially interested in challenges presented by "large magnitude", both in the dimension of data vectors and in the number of vector. Core areas of methodological research include multivariate mixtures, structural equations models, high-dimensional clustering and functional clustering. Key collaborative activities involve projects in immunology, modeling of climate-ecosystem dynamics and uncertainty quantification in AI approaches to medical image segmentation.

Research groups

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2014 | 2013 | 2012 | 2011 | 2010 | 2008 | 2007 | 2006 | 2005 | 2002
Number of items: 60.

2024

Wilkie, C., Ray, S. , Miller, C. and Scott, M. (2024) Investigating River Water Quality Using Network Distance Based Spatiotemporal Flexible Regression. In: 52nd Scientific Meeting of the Italian Statistical Society, Bari, Italy, 17-20 Jun 2024, (Accepted for Publication)

2023

Gemmell, A. J., Brown, C. M., Ray, S. and Small, A. (2023) Quantitative uptake in 99mTc-EDDA/HYNIC-TOC somatostatin receptor imaging – the effect of long-acting release somatostatin analogue therapy. Nuclear Medicine Communications, 44(11), pp. 944-952. (doi: 10.1097/MNM.0000000000001746) (PMID:37578312)

Zhang, W. and Ray, S. (2023) Deep Probability Contour Framework for Tumour Segmentation and Dose Painting in PET Images. In: 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Vancouver, Canada, 8-12 Oct 2023, pp. 534-543. ISBN 9783031439001 (doi: 10.1007/978-3-031-43901-8_51)

Cantoni, D. et al. (2023) Correlation between pseudotyped virus and authentic virus neutralisation assays, a systematic review and meta-analysis of the literature. Frontiers in Immunology, 14, 1184362. (doi: 10.3389/fimmu.2023.1184362) (PMID:37790941) (PMCID:PMC10544934)

Sekhar Sen, I. et al. (2023) Geochemical evolution of dissolved trace elements in space and time in the Ramganga River, India. Environmental Monitoring and Assessment, 195(10), 1150. (doi: 10.1007/s10661-023-11665-0) (PMID:37668950) (PMCID:37668950)

Zhang, W. and Ray, S. (2023) From coarse to fine: a deep 3D probability volume contour framework for tumor segmentation and dose painting in PET images. Frontiers In Radiology, 3, 1225215. (doi: 10.3389/fradi.2023.1225215)

Pascall, D. J. et al. (2023) Directions of change in intrinsic case severity across successive SARS-CoV-2 variant waves have been inconsistent. Journal of Infection, 87(2), pp. 128-135. (doi: 10.1016/j.jinf.2023.05.019) (PMID:37270070) (PMCID:PMC10234362)

Ho, A. et al. (2023) Adeno-associated virus 2 infection in children with non-A-E hepatitis. Nature, 617(7961), pp. 555-563. (doi: 10.1038/s41586-023-05948-2) (PMID:36996873)

Glendell, M., Sinha, R., Choudhary, B., Singh, M. and Ray, S. (2023) Probabilistic Modelling of Water Quality in the Ramganga River, India, Informed by Sparce Observational Data. EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023. (doi: 10.5194/egusphere-egu23-7990)

Pascall, D. J. et al. (2023) The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: a genomics-based retrospective cohort analysis. PLoS ONE, 18(4), e0284187. (doi: 10.1371/journal.pone.0284187) (PMID:37053201) (PMCID:PMC10101505)

Jones, K.A. , Paterson, C.A. , Ray, S. , Motherwell, D.W., Hamilton, D.J. , Small, A.D., Martin, W. and Goodfield, N.E.R. (2023) Beta-blockers and mechanical dyssynchrony in heart failure assessed by radionuclide ventriculography. Journal of Nuclear Cardiology, 30(1), pp. 193-200. (doi: 10.1007/s12350-022-03142-x) (PMID:36417121) (PMCID:PMC9984517)

Dangerfield, C. E. et al. (2023) Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK. Journal of Theoretical Biology, 557, 111332. (doi: 10.1016/j.jtbi.2022.111332) (PMID:36323393)

2022

Ray, S. , Banerjee, A., Swift, A., Fanstone, J. W., Mamalakis, M., Vorselaars, B., Wilkie, C., Cole, J., Mackenzie, L. S. and Weeks, S. (2022) A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest x-rays. Scientific Reports, 12, 18220. (doi: 10.1038/s41598-022-21803-2) (PMID:36309547) (PMCID:PMC9617052)

Willett, B. J. et al. (2022) Publisher Correction: SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7, 1709. (doi: 10.1038/s41564-022-01241-6) (PMID:36114232) (PMCID:PMC9483304)

Willett, B. J. et al. (2022) SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7(8), pp. 1161-1179. (doi: 10.1038/s41564-022-01143-7) (PMID:35798890) (PMCID:PMC9352574)

Zhang, W. and Ray, S. (2022) Kernel Smoothing-based Probability Contours for Tumour Segmentation. 26th UK Conference on Medical Image Understanding and Analysis (MIUA 2022), University of Cambridge, 27-29 July 2022.

Al Alawi, M., Ray, S. and Gupta, M. (2022) A New Functional Data Clustering Technique Based on Spectral Clustering and Downsampling. 17th Conference of the International Federation of Classification Societies (IFCS 2022), Porto, Portugal, 19-23 July 2022. ISBN 9789899895591

Zhang, W. and Ray, S. (2022) Kernel Smoothing-based Probability Contours for Tumour Segmentation. Classification and Data Science in Digital Age - 17th Conference of the International Federation of Classification Society (IFCS 2022), Porto, Portugal, 19-23 July 2022.

Boss, A. N. et al. (2022) Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers. International Journal of Molecular Sciences, 23(13), 7260. (doi: 10.3390/ijms23137260) (PMID:35806273) (PMCID:PMC9266863)

Zhang, W. and Ray, S. (2022) Analysis of Positron Emission Tomography Data for Tumour Detection and Delineation. 14th SINAPSE Annual Scientific Meeting, Glasgow, UK, 13-14 June 2022.

Jones, K.A. , Small, A.D., Ray, S. , Hamilton, D.J. , Martin, W., Robinson, J., Goodfield, N.E.R. and Paterson, C.A. (2022) Radionuclide ventriculography phase analysis for risk stratification of patients undergoing cardiotoxic cancer therapy. Journal of Nuclear Cardiology, 29(2), pp. 581-589. (doi: 10.1007/s12350-020-02277-z) (PMID:32748278)

2021

Mamalakis, M., Swift, A. J., Vorselaars, B., Ray, S. , Weeks, S., Ding, W., Clayton, R. H., Mackenzie, L. S. and Banerjee, A. (2021) DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. Computerized Medical Imaging and Graphics, 94, 102008. (doi: 10.1016/j.compmedimag.2021.102008) (PMCID:PMC8539634)

Garg, N. K., Ray, S. and Mathur, A. (2021) Abstract 10932: Prediction of 30-Day Hospital Readmission in High-Risk Atherosclerotic Cardiovascular Disease Patients Using Machine Learning Methods on Electronic Health Record Data from Medical Information Mart for Intensive Care-3 Database. Circulation, 144(Suppl1), A10932. (doi: 10.1161/circ.144.suppl_1.10932)

Wilkie, C., Ray, S. , Scott, M. and Miller, C. (2021) Bayesian Spatiotemporal Statistical Modelling of Water Quality within Rivers. EGU General Assembly 2021, 19-30 Apr 2021. (doi: 10.5194/egusphere-egu21-10843)

Wilkie, C., Ray, S. , Scott, M. , Miller, C. , Sinha, R. and Bowes, M. (2021) Statistical Downscaling for the Fusion of In-river, Drone and Satellite Water Quality Data in a River Network. 8th Channel Network Conference, 07-09 April 2021.

Mackenzie, L. S., Wilkie, C., Ray, S. , Banerjee, A., Mamalakis, M., Swift, A. J., Vorselaars, B., Fanstone, J. and Weeks, S. (2021) Can Kidney Function Be Used to Predict Survival of COVID-19 in Hospitals? Predictive Modelling in a Retrospective Cohort Study. Pharmacology 2021: Today's Science, Tomorrow's Medicines, 07-09 Sep 2021.

2020

Banerjee, A., Ray, S. , Vorselaars, B., Kitson, J., Mamalakis, M., Weeks, S., Baker, M. and Mackenzie, L. S. (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population. International Immunopharmacology, 86, 106705. (doi: 10.1016/j.intimp.2020.106705) (PMCID:PMC7296324)

Ray, S. , Scott, M. and Miller, C. (2020) Developing Statistical Downscaling to Improve Water Quality Understanding and Management in the Ramganga Sub-Basin. JSM 2020, 02-06 Aug 2020.

2019

Al Alawi, M., Ray, S. and Gupta, M. (2019) A New Framework for Distance-based Functional Clustering. In: 34th International Workshop on Statistical Modelling, Guimarães, Portugal, 07-12 Jul 2019,

Bayarri, M.J., Berger, J. O., Jang, W., Ray, S. , Pericchi, L. R. and Visser, I. (2019) Prior-based Bayesian information criterion. Statistical Theory and Related Fields, 3(1), pp. 2-13. (doi: 10.1080/24754269.2019.1582126)

Berger, J., Jang, W., Ray, S. , Rericchi, L. R. and Visser, I. (2019) Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser. Statistical Theory and Related Fields, 3(1), pp. 37-39. (doi: 10.1080/24754269.2019.1611147)

Ray, S. (2019) Analysis of PET Imaging for Tumor Delineation. 11th SINAPSE Annual Scientific Meeting, Dundee, UK, 21 Jun 2019.

Mangisa, S., Das, S., Ray, S. and Sharp, G. (2019) Functional regression models for South African economic indicators: a growth curve perspective. OPEC Energy Review, 43(2), pp. 217-237. (doi: 10.1111/opec.12148)

2018

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

2017

Liu, C., Ray, S. and Hooker, G. (2017) Functional principal component analysis of spatially correlated data. Statistics and Computing, 27(6), pp. 1639-1654. (doi: 10.1007/s11222-016-9708-4)

Labrosse, N. et al. (2017) Preparing for the Journey: Supporting Students to Make Successful Transitions Into and Out of Taught Postgraduate Study. 10th Annual University of Glasgow Learning and Teaching Conference, Glasgow, UK, 30 Mar 2017.

2014

Cheng, Y. and Ray, S. (2014) Parallel and hierarchical mode association clustering with an R package Modalclust. Open Journal of Statistics, 4(10), pp. 826-836. (doi: 10.4236/ojs.2014.410078)

Cheng, Y. and Ray, S. (2014) Multivariate modality inference using Gaussian kernel. Open Journal of Statistics, 4(5), pp. 419-434. (doi: 10.4236/ojs.2014.45041)

Lindsay, B. G., Markatou, M. and Ray, S. (2014) Kernels, degrees of freedom and power properties of quadratic distance goodness of fit tests. Journal of the American Statistical Association, 109(505), pp. 395-410. (doi: 10.1080/01621459.2013.836972)

Bollen, K. A., Harden, J. J., Ray, S. and Zavisca, J. (2014) BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 21(1), pp. 1-19. (doi: 10.1080/10705511.2014.856691)

Cheng, Y., Ray, S. , Chang, M. and Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value. Statistics in Biopharmaceutical Research, 6(3), pp. 241-250. (doi: 10.1080/19466315.2014.923324)

2013

Alexandrovich, G., Holzmann, H. and Ray, S. (2013) On the number of modes of finite mixtures of elliptical distributions. In: Lausen, B., Van den Poel, D. and Ultsch, A. (eds.) Algorithms from and for Nature and Life: Classification and Data Analysis. Series: Studies in Classification, Data Analysis, and Knowledge Organization, 2. Springer International Publishing, pp. 49-57. ISBN 9783319000350 (doi: 10.1007/978-3-319-00035-0_4)

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. (doi: 10.1111/j.1467-9876.2012.01066.x).

2012

Gupta, M. and Ray, S. (2012) Sequence pattern discovery with applications to understanding gene regulation and vaccine design. In: Rao, C.R., Chakraborty, R. and Sen, P.K. (eds.) Handbook of Statistics. Elsevier Press.

Bollen, K.A., Ray, S. , Zavisca, J. and Harden, J.J. (2012) A comparison of Bayes factor approximation methods including two new methods. Sociological Methods and Research, 41(2), pp. 294-324. (doi: 10.1177/0049124112452393)

Liu, C., Ray, S. , Hooker, G. and Friedl, M. (2012) Functional factor analysis for periodic remote sensing data. Annals of Applied Statistics, 6(2), pp. 601-624. (doi: 10.1214/11-AOAS518)

Ray, S. and Pyne, S. (2012) A computational framework to emulate the human perspective in flow cytometric data analysis. PLoS ONE, 7(5), e35693. (doi: 10.1371/journal.pone.0035693) (PMID:22563466) (PMCID:PMC3341382)

Ray, S. and Ren, D. (2012) On the upper bound of the number of modes of a multivariate normal mixture. Journal of Multivariate Analysis, 108, 41 - 52. (doi: 10.1016/j.jmva.2012.02.006)

2011

DeLuca, D.S., Marina, O., Ray, S. , Zhang, G.L., Wu, C.J. and Brusic, V. (2011) Data processing and analysis for protein microarrays. Methods in Molecular Biology, 723(7), pp. 337-347. (doi: 10.1007/978-1-61779-043-0_21)

Shi, P., Ray, S. , Zhu, Q. and Kon, M.A. (2011) Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction. BMC Bioinformatics, 12(1), p. 375. (doi: 10.1186/1471-2105-12-375)

2010

Ray, S. (2010) Discussion of "Projection pursuit via white noise matrices" by G. Hui and B. Lindsay. Sankhya B, 72(2), pp. 147-151. (doi: 10.1007/s13571-011-0008-x)

2008

Lin, H., Ray, S. , Tongchusak, S., Reinherz, E.L. and Brusic, V. (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunology, 9(1), p. 8. (doi: 10.1186/1471-2172-9-8)

Lindsay, B.G., Markatou, M., Ray, S. , Yang, K. and Chen, S.-C. (2008) Quadratic distances on probabilities: A unified foundation. Annals of Statistics, 36(2), pp. 983-1006. (doi: 10.1214/009053607000000956)

Ray, S. and Lindsay, B.G. (2008) Model selection in high dimensions: a quadratic-risk-based approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70(1), pp. 95-118. (doi: 10.1111/j.1467-9868.2007.00623.x)

2007

Li, J., Ray, S. and Lindsay, B.G. (2007) A nonparametric statistical approach to clustering via mode identification. Journal of Machine Learning Research: Proceedings Track, 8, pp. 1687-1723.

Levy, J. H., Reinhardt, J. M., Broadhurst, R. E., Ray, S. , Chaney, E. L. and Pizer, S. M. (2007) Signaling local non-credibility in an automatic segmentation pipeline. In: Medical Imaging 2007: Image Processing, San Diego, CA, USA, 17-22 Feb 2007, (doi: 10.1117/12.709015)

Ray, S. and Kepler, T.B. (2007) Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding. Immunome Research, 3(1), p. 9. (doi: 10.1186/1745-7580-3-9)

2006

Jeong, J., Pizer, S.M. and Ray, S. (2006) Statistics on anatomic objects reflecting inter-object relations. In: 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Copenhagen, 1 Oct 2006, pp. 136-145.

2005

Ray, S. and Lindsay, B.G. (2005) The topography of multivariate normal mixtures. Annals of Statistics, 33(5), pp. 2042-2065. (doi: 10.1214/009053605000000417)

2002

Basu, A., Ray, S. , Park, C. and Basu, S. (2002) Improved power in multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series D (The Statistician), 51(3), pp. 381-393. (doi: 10.1111/1467-9884.00325)

This list was generated on Sat Jun 15 16:00:16 2024 BST.
Number of items: 60.

Articles

Gemmell, A. J., Brown, C. M., Ray, S. and Small, A. (2023) Quantitative uptake in 99mTc-EDDA/HYNIC-TOC somatostatin receptor imaging – the effect of long-acting release somatostatin analogue therapy. Nuclear Medicine Communications, 44(11), pp. 944-952. (doi: 10.1097/MNM.0000000000001746) (PMID:37578312)

Cantoni, D. et al. (2023) Correlation between pseudotyped virus and authentic virus neutralisation assays, a systematic review and meta-analysis of the literature. Frontiers in Immunology, 14, 1184362. (doi: 10.3389/fimmu.2023.1184362) (PMID:37790941) (PMCID:PMC10544934)

Sekhar Sen, I. et al. (2023) Geochemical evolution of dissolved trace elements in space and time in the Ramganga River, India. Environmental Monitoring and Assessment, 195(10), 1150. (doi: 10.1007/s10661-023-11665-0) (PMID:37668950) (PMCID:37668950)

Zhang, W. and Ray, S. (2023) From coarse to fine: a deep 3D probability volume contour framework for tumor segmentation and dose painting in PET images. Frontiers In Radiology, 3, 1225215. (doi: 10.3389/fradi.2023.1225215)

Pascall, D. J. et al. (2023) Directions of change in intrinsic case severity across successive SARS-CoV-2 variant waves have been inconsistent. Journal of Infection, 87(2), pp. 128-135. (doi: 10.1016/j.jinf.2023.05.019) (PMID:37270070) (PMCID:PMC10234362)

Ho, A. et al. (2023) Adeno-associated virus 2 infection in children with non-A-E hepatitis. Nature, 617(7961), pp. 555-563. (doi: 10.1038/s41586-023-05948-2) (PMID:36996873)

Pascall, D. J. et al. (2023) The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: a genomics-based retrospective cohort analysis. PLoS ONE, 18(4), e0284187. (doi: 10.1371/journal.pone.0284187) (PMID:37053201) (PMCID:PMC10101505)

Jones, K.A. , Paterson, C.A. , Ray, S. , Motherwell, D.W., Hamilton, D.J. , Small, A.D., Martin, W. and Goodfield, N.E.R. (2023) Beta-blockers and mechanical dyssynchrony in heart failure assessed by radionuclide ventriculography. Journal of Nuclear Cardiology, 30(1), pp. 193-200. (doi: 10.1007/s12350-022-03142-x) (PMID:36417121) (PMCID:PMC9984517)

Dangerfield, C. E. et al. (2023) Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK. Journal of Theoretical Biology, 557, 111332. (doi: 10.1016/j.jtbi.2022.111332) (PMID:36323393)

Ray, S. , Banerjee, A., Swift, A., Fanstone, J. W., Mamalakis, M., Vorselaars, B., Wilkie, C., Cole, J., Mackenzie, L. S. and Weeks, S. (2022) A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest x-rays. Scientific Reports, 12, 18220. (doi: 10.1038/s41598-022-21803-2) (PMID:36309547) (PMCID:PMC9617052)

Willett, B. J. et al. (2022) Publisher Correction: SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7, 1709. (doi: 10.1038/s41564-022-01241-6) (PMID:36114232) (PMCID:PMC9483304)

Willett, B. J. et al. (2022) SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7(8), pp. 1161-1179. (doi: 10.1038/s41564-022-01143-7) (PMID:35798890) (PMCID:PMC9352574)

Boss, A. N. et al. (2022) Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers. International Journal of Molecular Sciences, 23(13), 7260. (doi: 10.3390/ijms23137260) (PMID:35806273) (PMCID:PMC9266863)

Jones, K.A. , Small, A.D., Ray, S. , Hamilton, D.J. , Martin, W., Robinson, J., Goodfield, N.E.R. and Paterson, C.A. (2022) Radionuclide ventriculography phase analysis for risk stratification of patients undergoing cardiotoxic cancer therapy. Journal of Nuclear Cardiology, 29(2), pp. 581-589. (doi: 10.1007/s12350-020-02277-z) (PMID:32748278)

Mamalakis, M., Swift, A. J., Vorselaars, B., Ray, S. , Weeks, S., Ding, W., Clayton, R. H., Mackenzie, L. S. and Banerjee, A. (2021) DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. Computerized Medical Imaging and Graphics, 94, 102008. (doi: 10.1016/j.compmedimag.2021.102008) (PMCID:PMC8539634)

Garg, N. K., Ray, S. and Mathur, A. (2021) Abstract 10932: Prediction of 30-Day Hospital Readmission in High-Risk Atherosclerotic Cardiovascular Disease Patients Using Machine Learning Methods on Electronic Health Record Data from Medical Information Mart for Intensive Care-3 Database. Circulation, 144(Suppl1), A10932. (doi: 10.1161/circ.144.suppl_1.10932)

Banerjee, A., Ray, S. , Vorselaars, B., Kitson, J., Mamalakis, M., Weeks, S., Baker, M. and Mackenzie, L. S. (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population. International Immunopharmacology, 86, 106705. (doi: 10.1016/j.intimp.2020.106705) (PMCID:PMC7296324)

Bayarri, M.J., Berger, J. O., Jang, W., Ray, S. , Pericchi, L. R. and Visser, I. (2019) Prior-based Bayesian information criterion. Statistical Theory and Related Fields, 3(1), pp. 2-13. (doi: 10.1080/24754269.2019.1582126)

Berger, J., Jang, W., Ray, S. , Rericchi, L. R. and Visser, I. (2019) Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser. Statistical Theory and Related Fields, 3(1), pp. 37-39. (doi: 10.1080/24754269.2019.1611147)

Mangisa, S., Das, S., Ray, S. and Sharp, G. (2019) Functional regression models for South African economic indicators: a growth curve perspective. OPEC Energy Review, 43(2), pp. 217-237. (doi: 10.1111/opec.12148)

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

Liu, C., Ray, S. and Hooker, G. (2017) Functional principal component analysis of spatially correlated data. Statistics and Computing, 27(6), pp. 1639-1654. (doi: 10.1007/s11222-016-9708-4)

Cheng, Y. and Ray, S. (2014) Parallel and hierarchical mode association clustering with an R package Modalclust. Open Journal of Statistics, 4(10), pp. 826-836. (doi: 10.4236/ojs.2014.410078)

Cheng, Y. and Ray, S. (2014) Multivariate modality inference using Gaussian kernel. Open Journal of Statistics, 4(5), pp. 419-434. (doi: 10.4236/ojs.2014.45041)

Lindsay, B. G., Markatou, M. and Ray, S. (2014) Kernels, degrees of freedom and power properties of quadratic distance goodness of fit tests. Journal of the American Statistical Association, 109(505), pp. 395-410. (doi: 10.1080/01621459.2013.836972)

Bollen, K. A., Harden, J. J., Ray, S. and Zavisca, J. (2014) BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 21(1), pp. 1-19. (doi: 10.1080/10705511.2014.856691)

Cheng, Y., Ray, S. , Chang, M. and Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value. Statistics in Biopharmaceutical Research, 6(3), pp. 241-250. (doi: 10.1080/19466315.2014.923324)

Bollen, K.A., Ray, S. , Zavisca, J. and Harden, J.J. (2012) A comparison of Bayes factor approximation methods including two new methods. Sociological Methods and Research, 41(2), pp. 294-324. (doi: 10.1177/0049124112452393)

Liu, C., Ray, S. , Hooker, G. and Friedl, M. (2012) Functional factor analysis for periodic remote sensing data. Annals of Applied Statistics, 6(2), pp. 601-624. (doi: 10.1214/11-AOAS518)

Ray, S. and Pyne, S. (2012) A computational framework to emulate the human perspective in flow cytometric data analysis. PLoS ONE, 7(5), e35693. (doi: 10.1371/journal.pone.0035693) (PMID:22563466) (PMCID:PMC3341382)

Ray, S. and Ren, D. (2012) On the upper bound of the number of modes of a multivariate normal mixture. Journal of Multivariate Analysis, 108, 41 - 52. (doi: 10.1016/j.jmva.2012.02.006)

DeLuca, D.S., Marina, O., Ray, S. , Zhang, G.L., Wu, C.J. and Brusic, V. (2011) Data processing and analysis for protein microarrays. Methods in Molecular Biology, 723(7), pp. 337-347. (doi: 10.1007/978-1-61779-043-0_21)

Shi, P., Ray, S. , Zhu, Q. and Kon, M.A. (2011) Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction. BMC Bioinformatics, 12(1), p. 375. (doi: 10.1186/1471-2105-12-375)

Ray, S. (2010) Discussion of "Projection pursuit via white noise matrices" by G. Hui and B. Lindsay. Sankhya B, 72(2), pp. 147-151. (doi: 10.1007/s13571-011-0008-x)

Lin, H., Ray, S. , Tongchusak, S., Reinherz, E.L. and Brusic, V. (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunology, 9(1), p. 8. (doi: 10.1186/1471-2172-9-8)

Lindsay, B.G., Markatou, M., Ray, S. , Yang, K. and Chen, S.-C. (2008) Quadratic distances on probabilities: A unified foundation. Annals of Statistics, 36(2), pp. 983-1006. (doi: 10.1214/009053607000000956)

Ray, S. and Lindsay, B.G. (2008) Model selection in high dimensions: a quadratic-risk-based approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70(1), pp. 95-118. (doi: 10.1111/j.1467-9868.2007.00623.x)

Li, J., Ray, S. and Lindsay, B.G. (2007) A nonparametric statistical approach to clustering via mode identification. Journal of Machine Learning Research: Proceedings Track, 8, pp. 1687-1723.

Ray, S. and Kepler, T.B. (2007) Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding. Immunome Research, 3(1), p. 9. (doi: 10.1186/1745-7580-3-9)

Ray, S. and Lindsay, B.G. (2005) The topography of multivariate normal mixtures. Annals of Statistics, 33(5), pp. 2042-2065. (doi: 10.1214/009053605000000417)

Basu, A., Ray, S. , Park, C. and Basu, S. (2002) Improved power in multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series D (The Statistician), 51(3), pp. 381-393. (doi: 10.1111/1467-9884.00325)

Book Sections

Alexandrovich, G., Holzmann, H. and Ray, S. (2013) On the number of modes of finite mixtures of elliptical distributions. In: Lausen, B., Van den Poel, D. and Ultsch, A. (eds.) Algorithms from and for Nature and Life: Classification and Data Analysis. Series: Studies in Classification, Data Analysis, and Knowledge Organization, 2. Springer International Publishing, pp. 49-57. ISBN 9783319000350 (doi: 10.1007/978-3-319-00035-0_4)

Gupta, M. and Ray, S. (2012) Sequence pattern discovery with applications to understanding gene regulation and vaccine design. In: Rao, C.R., Chakraborty, R. and Sen, P.K. (eds.) Handbook of Statistics. Elsevier Press.

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. (doi: 10.1111/j.1467-9876.2012.01066.x).

Conference or Workshop Item

Glendell, M., Sinha, R., Choudhary, B., Singh, M. and Ray, S. (2023) Probabilistic Modelling of Water Quality in the Ramganga River, India, Informed by Sparce Observational Data. EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023. (doi: 10.5194/egusphere-egu23-7990)

Zhang, W. and Ray, S. (2022) Kernel Smoothing-based Probability Contours for Tumour Segmentation. 26th UK Conference on Medical Image Understanding and Analysis (MIUA 2022), University of Cambridge, 27-29 July 2022.

Al Alawi, M., Ray, S. and Gupta, M. (2022) A New Functional Data Clustering Technique Based on Spectral Clustering and Downsampling. 17th Conference of the International Federation of Classification Societies (IFCS 2022), Porto, Portugal, 19-23 July 2022. ISBN 9789899895591

Zhang, W. and Ray, S. (2022) Kernel Smoothing-based Probability Contours for Tumour Segmentation. Classification and Data Science in Digital Age - 17th Conference of the International Federation of Classification Society (IFCS 2022), Porto, Portugal, 19-23 July 2022.

Zhang, W. and Ray, S. (2022) Analysis of Positron Emission Tomography Data for Tumour Detection and Delineation. 14th SINAPSE Annual Scientific Meeting, Glasgow, UK, 13-14 June 2022.

Wilkie, C., Ray, S. , Scott, M. and Miller, C. (2021) Bayesian Spatiotemporal Statistical Modelling of Water Quality within Rivers. EGU General Assembly 2021, 19-30 Apr 2021. (doi: 10.5194/egusphere-egu21-10843)

Wilkie, C., Ray, S. , Scott, M. , Miller, C. , Sinha, R. and Bowes, M. (2021) Statistical Downscaling for the Fusion of In-river, Drone and Satellite Water Quality Data in a River Network. 8th Channel Network Conference, 07-09 April 2021.

Mackenzie, L. S., Wilkie, C., Ray, S. , Banerjee, A., Mamalakis, M., Swift, A. J., Vorselaars, B., Fanstone, J. and Weeks, S. (2021) Can Kidney Function Be Used to Predict Survival of COVID-19 in Hospitals? Predictive Modelling in a Retrospective Cohort Study. Pharmacology 2021: Today's Science, Tomorrow's Medicines, 07-09 Sep 2021.

Ray, S. , Scott, M. and Miller, C. (2020) Developing Statistical Downscaling to Improve Water Quality Understanding and Management in the Ramganga Sub-Basin. JSM 2020, 02-06 Aug 2020.

Ray, S. (2019) Analysis of PET Imaging for Tumor Delineation. 11th SINAPSE Annual Scientific Meeting, Dundee, UK, 21 Jun 2019.

Labrosse, N. et al. (2017) Preparing for the Journey: Supporting Students to Make Successful Transitions Into and Out of Taught Postgraduate Study. 10th Annual University of Glasgow Learning and Teaching Conference, Glasgow, UK, 30 Mar 2017.

Conference Proceedings

Wilkie, C., Ray, S. , Miller, C. and Scott, M. (2024) Investigating River Water Quality Using Network Distance Based Spatiotemporal Flexible Regression. In: 52nd Scientific Meeting of the Italian Statistical Society, Bari, Italy, 17-20 Jun 2024, (Accepted for Publication)

Zhang, W. and Ray, S. (2023) Deep Probability Contour Framework for Tumour Segmentation and Dose Painting in PET Images. In: 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Vancouver, Canada, 8-12 Oct 2023, pp. 534-543. ISBN 9783031439001 (doi: 10.1007/978-3-031-43901-8_51)

Al Alawi, M., Ray, S. and Gupta, M. (2019) A New Framework for Distance-based Functional Clustering. In: 34th International Workshop on Statistical Modelling, Guimarães, Portugal, 07-12 Jul 2019,

Levy, J. H., Reinhardt, J. M., Broadhurst, R. E., Ray, S. , Chaney, E. L. and Pizer, S. M. (2007) Signaling local non-credibility in an automatic segmentation pipeline. In: Medical Imaging 2007: Image Processing, San Diego, CA, USA, 17-22 Feb 2007, (doi: 10.1117/12.709015)

Jeong, J., Pizer, S.M. and Ray, S. (2006) Statistics on anatomic objects reflecting inter-object relations. In: 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Copenhagen, 1 Oct 2006, pp. 136-145.

This list was generated on Sat Jun 15 16:00:16 2024 BST.

Grants

Innovate UK: Sub-millimetre accuracy of 3D measurements and texture analysis of Diabetic Foot Ulcers (£50,000) 2023 Role: PI

Health Data Research UK: Evaluation of Variants Affecting Deployed COVID-19 Vaccines (£250,000)2021 - 2022 Role: Co-I 

University of Glasgow Reinvigorating Research Funding: (£40,000) 2022-2023 Role: PI

Scottish Funding Council COVID Funding: (£9,700) 2020-2021 Role: PI

EPSRC IAA (EP/R511705/1) Finger prick test for early prediction of SARS-CoV-2; a screening method using changes in full blood count parameters (£3,000) 2020-2021 Role: PI

EPSRC GCRF grant: Developing statistical downscaling to improve water quality understanding and management in the Ramganga sub-basin 1/10/2019 – 30/06/2022 (£ 461,314) Role: PI

NERC grant: A digital environment for water resources1/10/2019 to 1/10/2020 (£228,806) Role: Co-I

EPSRC-Industry studentship: Generation of synthetic medical histories for clinical decision support - a connected approach (£30,000) Role: PI 2018-2021

Scottish Funding Council: Datalab MSc Scholarship (£87,360) 01/10/201-30/09/2019

 Scottish Funding Council: Datalab MSc Scholarship (£27,800) 01/10/2016-30/09/2018

 European Social Fund: Datalab MSc Scholarship (£96,360) 01/10/2018-30/09/2020

 EPSRC (SECURE Feasibility Project No: FP2016002LP):Improved approaches for mapping and modelling blanket peatland extent and depth (£24,962)

Banff International Research Station for Mathematical Innovation and Discovery workshop grant: Frontiers in Functional Data Analysis. For operation reasons, this grant was administered by Banff International Research Station, Banff, Canada (£ 70,000)

EPSRC and DST (India) workshop grant: Solving Big Data Challenges in Modern Science through Statistical Modelling data Analysis. For operational reasons this grant was administered through International Centre for Mathematical Sciences (ICMS), Edinburgh, U. K. Co-organizer: Mayetri Gupta (£ 50,000)

EU ERASMUS Mobility Grant: Training Course on Functional Data at University of Bologna, July 2017 (£GBP 1700)

NSF (USA) Award No: #0934739: Functional Data Modeling of Climate-Ecosystem Dynamics 09/01/09- 08/31/13 ($363,851)

NSF (USA) Award No: #0947950: NSF   GK-12 Graduate STEM Fellows in K-12 Education GLACIER-Global Change Initiative-Education & Research 03/15/2010- 03/14/2014 ($2,854,102)

Supervision

  • Dantas De Oliveira Rolim, Gabriel
    Short-term forecast uncertainty in future low-carbon energy systems
  • Mandal, Adhiraj
    An Investigation into Distribution of Random Functions and Model-Based Clustering for Functional Data
  • Zhang, Wenhui
    Deep Probability Contour-based Tumour Segmentation and Uncertainty Quantification in Positron Emission Tomography Imaging

Teaching

2022-Semester II

  • Predictive Modeling
  • Functional Data Analysis

 

Professional activities & recognition

Grant committees & research advisory boards

  • 2015: Peer Review College,

Additional information

  • Member of Gateway Advisory Board  (Newton Gateway to Mathematics) Isaac Newton Institute for Mathematical Sciences: Cambridge, Cambridgeshire, GB 
  • Full member of Peer-review college of Engineering and Physical Sciences Research Council
  • Full member of Peer-review college of Natural Environment Research Council