Professor Dave Woods

Professor of Statistics, Head of Statistics

Dave Woods is a Professor of Statistics in the Southampton Statistical Sciences Research Institute (S3RI) and Mathematical Sciences. His research interests focus on the design and analysis of both physical and computer experiments, Bayesian methods, and the application of Statistics to science and technology. Much of his work is interdisciplinary and involves collaborations with researchers from other disciplines, and with government and industry. From 2012-2017, he held an EPSRC Fellowship.

Current position

Professor of Statistics

Previous position

Reader in Statistics, 2011 - 2013.

Qualifications

PhD in Statistics, University of Southampton

Research

Responsibilities

Publications

Teaching

Contact

Research interests

My research interests are in the design and analysis of experiments, particularly the development of new methods and criteria for design selection and assessment under linear and nonlinear models. A particular emphasis of my work is finding efficient designs when there is uncertainty in one or more aspects of the model for the response. I develop methodology that combines theory and computation to solve problems motivated by real experiments in science and industry. Application areas include engineering, chemistry and the pharmaceutical, automotive and aeronautics industries.

Research group

Statistics

Research project(s)

Design and Analysis of Experiments

Prediction of thermophysical properties of pharmeceutical compounds

Internal:

Head of Statistics
S3RI Research Theme Coordinator for Design and Analysis of Experiments

External:
Associate Editor for Technometrics

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Articles

Book Chapter

Woods, D., & Lewis, S. (2017). Design of experiments for screening. In R. Ghanem, D. Higdon, & H. Owhadi (Eds.), Handbook of Uncertainty Quantification (1 ed.). Springer International.

Conferences

Woods, D. C., Grove, D. M., Liccardi, I., Lewis, S. M., & Frey, J. G. (2006). An eLearning website for the design and analysis of experiments with application to chemical processes. In A. Rizzi, & M. Vichi (Eds.), COMPSTAT 2006: Proceedings In Computational Statistics (pp. 1641-1649). Physica-Verlag.
Woods, D. C., & Lewis, S. M. (2005). Designing experiments for binary data using search algorithms. In Proceedings of the 55th Session of the International Statistical Institute, Sydney 5-12 April 2005 International Statistical Institute.
Woods, D. C. (2005). Designs for generalized linear models under model uncertainty. International Conference on Design of Experiments, .
Woods, D. C. (2003). A Monte Carlo exchange algorithm for finding near-optimal designs under model contamination. Poster session presented at International Biometric Society British Region Conference, .
Woods, D. C. (2003). Minimum bias designs under random contamination: application to polynomial spline models. Conference on New Directions in Experimental Design DAE 2003, .
Ward, S. C., Hursthouse, M. B., Woods, D. C., & Lewis, S. M. (2003). Systematic study into the salt formation of functionalised organic substrates. In S. J. Cox (Ed.), Proceedings of UK e-Science All Hands Meeting (pp. 208-211). Engineering and Physical Sciences Research Council.
Ward, S. C., Hursthouse, M. B., Woods, D. C., & Lewis, S. M. (2003). Systematic Study into the Salt Formation of Functionalised Organic Substrates: Nottingham 2003 E-Science Poster. Poster session presented at E-Science All Hands Meeting, .

Letter/Editorial

Woods, D. (2018). Discussion of “Design augmentation for response optimization and model estimation”. Quality Engineering, 30(1), 57-59. https://doi.org/10.1080/08982112.2017.1383120

Report

McNamara, C. A., Woods, D. C., Lewis, S. M., Bradley, M., & Frey, J. G. (2005). Optimization of asymmetric dihydroxylation through optimal designed experiments. (School of Mathematics Technical Report; No. 386). University of Southampton, School of Mathematics.

Working Papers

Atkinson, A. C., & Woods, D. C. (2013). Handbook of the design and analysis of experiments: designs for generalized linear models. Chapman and Hall/CRC.
Overstall, A. M., & Woods, D. C. (2011). Bayesian lightweight emulators for multivariate computer models. (S3RI Methodology Working Papers; No. M11/01). Southampton Statistical Sciences Research Institute.
Draguljic, D., Woods, D. C., Dean, A. M., Lewis, S. M., & Vine, A. E. (2011). Screening strategies in the presence of interactions. (Southampton Statistical Sciences Research Institute Working Papers; No. M11/10). Southampton Statistical Sciences Research Institute, University of Southampton.
Biedermann, S., & Woods, D. C. (2009). Optimal designs for generalised nonlinear models with application to second harmonic generation experiments. (S3RI Methodology Working Papers; No. M09/19). Southampton Statistical Sciences Research Institute.
Biedermann, S., Dette, H., & Woods, D. C. (2009). Optimal designs for multivariable spline models. (S3RI Methodology Working Papers; No. M09/16). University of Southampton, Southampton Statistical Sciences Research Institute.
Russell, K. G., Woods, D. C., Lewis, S. M., & Eccleston, J. A. (2008). D-optimal designs for Poisson regression models. (S3RI Methodology Working Papers; No. M08/01). Southampton Statistical Sciences Research Institute.
Woods, D. C. (2008). Robust Designs For Binary Data: Applications Of Simulated Annealing. (S3RI Methodology Working Papers; No. M08/03). Southampton Statistical Sciences Research Institute.
Waterhouse, T. H., Woods, D. C., Eccleston, J. A., & Lewis, S. M. (2006). Design selection criteria for discrimination between nested models for binomial data. (S3RI Methodology Working Papers; No. M06/02). Southampton Statistical Sciences Research Institute.

MATH6157 Applied Statistical Modelling

Professor Dave Woods
Building 54 Mathematical Sciences University of Southampton Highfield Southampton SO17 1BJ

Room Number NNN: 39/3023

Facsimile: (023) 8059 5147

Professor Dave Woods's personal home page

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