Biography

Ian Dryden’s main area of research is the development of statistical methodology in highly-structured data analysis, including shapes, images and functional data. He has published over 150 articles and two joint books: Statistical Shape Analysis (2016) and Object Oriented Data Analysis (2022).

Dr Dryden was awarded a Ph.D. in 1989 from the University of Leeds and has taught and carried out research at Florida International University, University of Nottingham, University of Leeds and University of Chicago, in addition to two periods at University of South Carolina. He has been PI/Co-I of more than $20M in grants, and he is an elected fellow of the Institute of Mathematical Statistics.

References

Marron, J.S. and Dryden, I.L. (2022). Object-Oriented Data Analysis. CRC Press/Chapman and Hall, Boca Raton. 424 + xii pages.

Severn, K. E., Dryden, I. L. and Preston, S. P. (2022). Manifold valued data analysis of samples of
networks, with applications in corpus linguistics. Annals of Applied Statistics, 16, 368–390.

Seymour, R.G., Sirl, D., Preston, S.P., Dryden, I.L., Ellis, M.J.A, Perrat, B. and Goulding, J. (2022). The Bayesian spatial Bradley–Terry model: urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society, Series C, 71, 288-308.  https://rss.onlinelibrary.wiley.com/doi/10.1111/rssc.12532

Severn, K. E., Dryden, I. L. and Preston, S. P. (2021). Non-parametric regression for networks. Stat 10, e373  https://doi.org/10.1002/sta4.373

Kim, K., Dryden, I.L., Le, H. and Severn, K.E. (2021). Smoothing splines on Riemannian manifolds, with applications to 3D shape space. Journal of the Royal Statistical Society, Series B. 83, 108–132. https://doi.org/10.1111/rssb.12402  First published online: December 2nd, 2020.

Dryden, I.L., Kume, A., Paine, P.J. and Wood, A.T.A. (2021). Regression modelling for size-and-shape data based on a Gaussian model for landmarks. Journal of the American Statistical Association 116,  1011–1022. First published online: March 30th, 2020.  https://doi.org/10.1080/01621459.2020.1724115

Dryden, I.L., Kim, K., Laughton, C.A. and Le, H. (2019). Principal nested shape space analysis of molecular dynamics data. Annals of Applied Statistics, 13, 2213–2234.  https://doi.org/10.1214/19-AOAS1277

Dryden, I.L., Kim, K. and Le, H. (2019). Bayesian linear size-and-shape regression with applications to face data. Sankhya A, 81, 83–103.  https://doi.org/10.1007/s13171-018-0136-8 .

Lewis, N. H., Hitchcock, D. B., Dryden, I. L. and Rose, J. R. (2018). Peptide Refinement Using A  Stochastic Search. Journal of the Royal Statistical Society, Series C. 67, 1207–1236.  https://doi.org/10.1111/rssc.12280

Dryden, I. L. and Mardia, K. V. (2016). Statistical Shape Analysis, with Applications in R (Second Edition) John Wiley, Chichester. 454 + xxiii pages. Marron, J.S. and Dryden, I.L. (2022). Object-Oriented Data Analysis. CRC Press/Chapman and Hall,
Boca Raton. 424 + xii pages.