## Dr Antony Overstall## Associate Professor in StatisticsMathematical Sciences University of Southampton Southampton SO17 1BJ Tel: +44 (0) 23 8059 2724 E-mail: A.M.Overstall@soton.ac.uk |

- optimal experimental design;
- the analysis of categorical data.

Optimal experimental design involves allocating the (often, limited) resources of a physical experiment to, essentially, maximise the amount of "information" that the experiment provides. Increasingly, I am interested in phenomena which are explained by a model which is implemented by some computationally expensive computer code.

I am also interested in categorical data analysis, particularly incomplete contingency tables. The main application of these has been estimating the number of people who inject drugs in England and Scotland.

- Michaelides, D., Adamou, M., Woods, D.C. & Overstall, A.M. (2021). Optimal designs for experiments for scalar-on-function linear models. arXiv:2110.09115
- Dehideniya, M., Overstall, A.M., Drovandi, C.C. & McGree J.M. (2019). A synthetic likelihood-based Laplace approximation for efficient design of biological processes. arXiv:1903.04168

*Robust Bayesian Design of Experiments for Calibration of Mathematical Models*. Invited talk. SIAM Conference on Computational Science and Engineering (Virtual). 5th March 2021.*Challenges of estimating human population sizes*. Invited talk. International Biometric Society: Presidential Address and Annual General Meeting (Virtual). 11th November 2020.*Bayesian prediction for physical models with application to the optimisation of the synthesis of pharmaceutical products using chemical kinetics*. Statistics Seminar. School of Mathematical Sciences and Actuarial Science, University of Kent, Canterbury, UK. 23rd January 2020.*Bayesian Optimal Design for Ordinary Differential Equation Models*.Invited Talk. 12th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of London, UK. 16th December 2019*Bayesian design for intractable likelihood models*. Invited Talk. 10th International Workshop on Simulation and Statistics, University of Salzburg, Salzburg, Austria. 5th September 2019.*Bayesian design for physical models using computer experiments*. Invited Talk. Spring Research Conference on Statistics in Industry and Technology. Virginia Tech, Blacksburg, Virginia, USA. 22nd May 2019.*Bayesian design for physical models using computer experiments*. Invited Talk. 5th International Conference on Design of Experiments. University of Memphis, Memphis, Tennessee, USA. 20th May 2019.*Bayesian design for intractable likelihood models using computer experiments*. Statistics Seminar. Department of Applied Statistics, Johannes Kepler University, Linz, Austria. 4th April 2019.*Bayesian design for intractable likelihood models*. Statistics Seminar. Department of Mathematics, King's College, London, UK. 28th March 2019.*Bayesian prediction for physical models with application to the optimisation of the synthesis of pharmaceutical products using chemical kinetics*. Statistics Seminar. School of Mathematics, University of Edinburgh, Edinburgh, UK. 16th November 2018.*Bayesian design for intractable models*. Invited Talk. Joint Statistical Meetings, Vancouver, British Columbia, Canada. 1st August 2018.*Bayesian design for intractable models*. Invited Talk. International Symposium on Business and Industrial Statistics (ISBIS), University of Piraeus, Piraeus, Greece. 5th July 2018.*Bayesian design for intractable models*. Invited Talk. 2nd International Conference on Econometrics and Statistics (ECOSTAT), City University of Hong Kong, Hong Kong. 20th June 2018.*Experiments, statistics and uncertainty quantification*. Invited Talk. London Mathematical Society Summer School, University of Manchester, UK. 21st July 2017.*Optimal design for supersaturated experiments*. Invited Talk. 4th Greco-Italian Meeting on Statistics, Università degli Studi di Firenze, Florence, Italy. 4th July 2017.*Bayesian optimal design of experiments for models based on systems of ODEs*. Invited Talk. Statistical Perspectives on Uncertainty Quantification, Georgia Institute of Technology, Atlanta, Georgia, USA. 30th May 2017.*Bayesian optimal design of experiments using normal-based approximations to posterior quantities*. Invited Talk. Conference on Experimental Design and Analysis, Academia Sinica, Taipei, Taiwan. 17th December 2016.*Bayesian Optimal Design for Ordinary Differential Equation Models*. Statistics Seminar. Escuela de Arquitectura, Universidad Castilla La Mancha, Toledo, Spain. 10th November 2016.*Bayesian Optimal Design for Ordinary Differential Equation Models*. Statistics Seminar. School of Mathematics, University of Manchester, Manchester, UK. 3rd November 2016.*Bayesian optimal design of experiments for models based on systems of ODEs*. Invited Talk. SIAM Conference on Uncertainty Quantification, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. 8th April 2016.*Bayesian optimal design of experiments for models based on systems of ODEs*. Invited Talk. International Association for Statistical Computing Asian Region Section Conference, National University of Singapore, Singapore. 19th December 2015.*Bayesian optimal design for ordinary differential equation models*. Invited Talk. Designed Experiments: Recent Advances in Methods and Applications, University of Technology Sydney, Sydney, New South Wales, Australia. 14th December 2015.*Approximate Coordinate Exchange (ACE) Algorithm for Bayesian Optimal Design*. Invited Talk. Bayesian Optimal Design of Experiments (BODE) Workshop, Queensland University of Technology, Brisbane, Queensland, Australia. 10th December 2015.*Bayesian optimal design of experiments for models based on systems of ODEs*. Invited Talk. Bayes on the Beach, Surfers Paradise, Queensland, Australia. 9th December 2015.*Bayesian Optimal Design for Ordinary Differential Equation Models*. Statistics Seminar. School of Mathematics & Statistics, Newcastle University, Newcastle, UK. 30th October 2015.*Estimating the prevalence of injecting drug use in Scotland using capture-recapture and partially observed contingency tables.*Invited Talk. World Statistics Congress, Rio de Janeiro, Brazil. 28th July 2015.*Bayesian optimal design of experiments for models based on systems of ODEs.*Invited Talk. 3rd Greco-Italian Meeting on Statistics, Athens, Greece. 26th June 2015.*Bayesian optimal design for ordinary differential equation models.*Statistics Seminar. Biomathematics and Statistics Scotland (BioSS), James Hutton Institute, Aberdeen, UK. 2nd June 2015.*Bayesian optimal design for computationally expensive models*. Statistics Seminar. Mathematics Sciences, University of Southampton, Southampton, UK. 13th November 2014.*Bayesian Inference and Optimal Design for Differential Equation Models with Application to Chemical Kinetics*. Invited Talk. Joint Statistical Meetings, Boston, Massachusetts, USA. 5th August 2014.*Bayesian optimal design for estimating the physical parameters of differential equation models*. Statistics Seminar. Department of Statistics, University of Oxford, Oxford, UK. 4th June 2014.*The approximate coordinate exchange algorithm for Bayesian optimal experimental design*. Statistics Seminar. Department of Mathematics and Statistics, Lancaster University, Lancaster, UK. 28th March 2014.*A Strategy for Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties*. Statistics Seminar. CSIRO/Mathematics Sciences, Australian National University, Canberra, Australia. 5th July 2013.*Optimal Bayesian Design using Gaussian Process Emulators*. Invited Talk. Spring Research Conference on Statistics in Industry and Technology. UCLA, Los Angeles, California, USA. 22nd June 2013.*A Strategy for Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties*. Statistics Seminar. Mathematics Sciences, University of Southampton, Southampton, UK. 6th December 2012.*Bayesian Lightweight Emulation of a Multivariate Simulator for a Humanitarian Relief Scenario*. Invited Talk. Spring Research Conference on Statistics in Industry and Technology. Northwestern University, Evanston, Illinois, USA. 23rd June 2011.

*Decision-theoretic frequentist optimal design of experiments*. Contributed Talk. Joint Statistical Meetings, Chicago, Illinois, USA. 31st July 2016.*Bayesian optimal design for estimating physical parameters of computer models with application to measuring properties of human placentas*. Poster. DAE2015: Design and Analysis of Experiments Conference, SAS World Headquarters, Cary, North Carolina, USA, 5th March 2015.*Bayesian optimal design for estimating the physical parameters of computer models based on a system of ordinary differential equations*. Contributed Talk. Uncertainty in Computer Models Conference. University of Sheffield, Sheffield, UK. 29th July 2014.*Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties*. Contributed Talk. Western and North American Region of the International Biometrics Society Conference. UCLA, Los Angeles, California, USA. 17th June 2013.*Design space production for chemical kinetics models*. Poster. Turing Gateway to Mathematics: Industrial Statistics Day, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK. 25th March 2013.*Emulating the Likelihood/Posterior Function via Sequential Design*. Contributed Talk. Joint Statistical Meetings. South Beach, Miami, Florida, USA. 3rd August 2011.

- Hendriico Merilla
**Topics in Design of Experiments** - Damianos Michaelides
**Functional Design of Experiments**

- Altea Lorenzo-Arribas
**Statistical Methods for Analysis of Ordinal Response Data**(Graduated 2019) - Meshayil Meshal R Alsolmi
**Decision-Theoretic Design of Experiments**(Viva passed 2019)

- conting R package for Bayesian analysis of contingency tables. Version 1.7. 2nd April 2019.
- acebayes R package for Optimal Bayesian Experimental Design using the ACE Algorithm. Version 1.8. 30th September 2019

- From 2020 to Present: Co-opted committee member of the Computational Statistics and Machine Learning section of the Royal Statistical Society.
- From 2020 to Present: External examiner for undergraduate and postgraduate (taught) statistics programmes at the University of St Andrews.
- From 2021 to Present: Associate editor of Journal of the Royal Statistical Society Series C (Applied Statistics).
- I organised and chaired the invited session Optimal Experimental Design for Physical Models which took place at the Joint Statistical Meetings (JSM) in Chicago in July/August 2016. This session was sponsored by the American Statistical Association's Section on Physical and Engineering Sciences.
- I am a co-organiser of the MSG seminar series on design of experiments.
- I was a co-organiser of the Bayesian Optimal Design of Experiments (BODE) workshop which took place at Queensland University of Technology, Brisbane, Australia in December 2015.
- From 2015 to 2019, I led the Statistical Modelling module on APTS.
- I serve on the Advisory Committee of APTS.
- From 2014 to 2017, I served on the Executive Committee of APTS.
- I was on the local organising committee of the 4th Channel Network Conference for the British and Irish Region of the International Biometric Society, 3rd-5th July 2013.

- Overstall, A.M. (2021). Properties of using Fisher information gain for Bayesian design of experiments.
*Journal of Statistical Planning and Inference***(To appear)** - Overstall, A.M. & McGree J.M. (2021). Bayesian decision-theoretic design of experiments under an alternative model.
*Bayesian Analysis***(To appear)** - Cruyff, M., Overstall, A.M., Papathomas, M, & McCrea, R. (2021). Multiple System Estimation of Victims of Human Trafficking: Model Assessment and Selection.
*Crime & Delinquency***(To appear)** - Sharifi Far, S., King, R., Bird, S., Overstall, A.M., Worthington, H., Jewell, N. (2021). Multiple Systems Estimation for Modern Slavery: Robustness of List Omission and Combination.
*Crime & Delinquency***(To appear)** - Senarathne, J.S.G., Overstall, A.M. & McGree J.M. (2020). Bayesian adaptive N-of-1 trials for estimating population and individual treatment effects.
*Statistics in Medicine***39**(29) 4499-4518 - Overstall, A.M., Woods, D.C. & Adamou, M. (2020). acebayes: An R Package for Bayesian Optimal Design of Experiments via Approximate Coordinate Exchange.
*Journal of Statistical Software***95**(13) 1-33 - Overstall, A.M., Woods, D.C. & Parker, B.M. (2020). Bayesian optimal design for ordinary differential equation models with application in biological science.
*Journal of the American Statistical Association***115**583-598 - Overstall, A.M., & McGree, J.M. (2020). Bayesian design of experiments for intractable likelihood models using coupled auxiliary models and multivariate emulation.
*Bayesian Analysis***15**(1) 103-131 - Overstall, A.M., Woods, D.C. & Martin, K.J. (2019). Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics.
*Computational Statistics and Data Analysis***132**126-142. - Heck, D.W., Overstall, A.M., Gronau, Q.F. & Wagenmakers, E. (2019). Quantifying Uncertainty in Transdimensional Markov Chain Monte Carlo Using Discrete Markov Models.
*Statistics and Computing***29**(4) 631-643 - Overstall, A.M., McGree, J.M. & Drovandi, C.C. (2018). An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions.
*Statistics and Computing***28**(2) 343-358 - Overstall, A.M. & Woods, D.C. (2017). Bayesian Design of Experiments using Approximate Coordinate Exchange.
*Technometrics***59**458-470 - Woods, D.C., Overstall, A.M., Adamou, M., & Waite, T.W. (2017). Bayesian design of experiments for generalised linear models and dimensional analysis with industrial and scientific application (Invited paper with Discussion)
*Quality Engineering***29**(1) 91-103 - Overstall, A.M. & Woods, D.C. (2016). Multivariate emulation of computer simulators: model selection and diagnostics with application to a humanitarian relief model.
*Journal of the Royal Statistical Society Series C***65**(4) 483-505 - King, R. & Overstall, A.M. (2015). Population Size Estimation and Capture-Recapture Methods.
*International Encyclopedia of the Social & Behavioral Sciences (Second Edition)*. 603-608. - Overstall, A.M. & King, R. (2014). conting: an R package for Bayesian analysis of complete and incomplete contingency tables.
*Journal of Statistical Software*.**58**(7) 1-27. - Overstall, A.M., King, R., Bird, S.M., Hutchinson, S.M. & Hay, G. (2014). Incomplete contingency tables with censored cells with application to estimating the number of people who inject drugs in Scotland.
*Statistics in Medicine*.**33**(9) 1564-1579. - King, R., Bird, S.M., Overstall, A.M., Hay, G. & Hutchinson, S.M. (2014). Estimating prevalence of injecting drug users and associated heroin-related death rates in England by using regional data and incorporating prior information.
*Journal of the Royal Statistical Society Series A*.**177**(1) 209-236. - Overstall, A.M., & King, R. (2014). A default prior distribution for contingency tables with dependent factor levels.
*Statistical Methodology*.**16**(1) 90-99. - King, R., Bird, S.M., Overstall, A.M., Hay, G. & Hutchinson, S.M. (2013). Injecting drug users in Scotland, 2006: listing, number, demography, and opiate-related death-rates.
*Addiction Research and Theory*.**21**(3) 235-246. - Overstall, A.M. & Woods, D.C. (2013). A Strategy for Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties.
*Biometrics*.**69**(2) 458-468. - Forster, J.J., Gill, R.C. & Overstall, A.M. (2012). Reversible jump methods for generalised linear models and generalised linear mixed models.
*Statistics and Computing*.**22**(1) 107-120. - Overstall, A.M. & Forster, J.J. (2010). Default Bayesian model determination methods for generalised linear mixed models.
*Computational Statistics and Data Analysis*.**54**(12) 3269-3288.