David C. Woods

2.1k citations

80 papers · 1.5k indexed · h-index 21

Impact in

Atmospheric Science top 5%
- Atmospheric chemistry and aerosols
- Atmospheric Ozone and Climate
Management Science and Operations Research top 1%
- Optimal Experimental Design Methods

Papers in

Management Science and Operations Research 37
- Optimal Experimental Design Methods 34
Statistics, Probability and Uncertainty 17
- Probabilistic and Robust Engineering Design 15

Co-authors: Raymond L. Chuan William I. Rose Antony M. Overstall J. A. Eccleston K. G. Russell S. M. Lewis R. D. Cadle Peter van de Ven
Journals: Geophysical Research Letters (5 papers)Science (4 papers)Technometrics (4 papers)Journal of Geophysical Research Atmospheres (3 papers)Computers & Chemical Engineering (3 papers)
Partner nations: United Kingdom United States Australia

In The Last Decade

David C. Woods

75 papers receiving 1.3k citations

Peers

Replace James L. Martin with:

James L. Martin United States

J. Rosiński United States

Zhongguo ke xue yuan

B.A. Robinson United States

Gardar Johannesson United States

Blaza Toman United States

Philip Jonathan United Kingdom

Serge Guillas United Kingdom

William Kleiber United States

Mathieu Ribatet France

David C. Woods relative to James L. Martin United States James L. Martin's profile →

Citations per field

00.5×5×10.5×

James L. Martin · 1×

×8.1 607/75

AS

×11 421/40

MSOR

×1.3 200/151

SPU

×5.6 382/68

CTM

×2.8 487/172

GPC

Citations per year

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2026

Countries citing papers authored by David C. Woods

Since Specialization

Citations

This map shows the geographic impact of David C. Woods's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David C. Woods with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David C. Woods more than expected).

Fields of papers citing papers by David C. Woods

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David C. Woods. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David C. Woods. The network helps show where David C. Woods may publish in the future.

Co-authors

The 25 scholars most cited alongside David C. Woods, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David C. Woods Line = papers co-authored together David C. Woods links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Optimal design of dynamic experiments for scalar-on-function linear models with application to a biopharmaceutical study Biometrics ·T. Z. Song, Sri Megawati Mohungo, David C. Woods, Antony M. Overstall	2026	0
2	Multi-objective reaction optimization under uncertainties using expected quantile improvement Computers & Chemical Engineering ·فرناز ملکی فرد, Dong Zhengmou, Yoshihiko Abe, David C. Woods, Alexei A. Lapkin	2025	3
3	Machine learning-guided space-filling designs for high throughput liquid formulation development Computers & Chemical Engineering ·陈昌智, Dong Zhengmou, David C. Woods, Alexei A. Lapkin	2025	2
4	Multiobjective Optimization Using Expected Quantile Improvement for Decision Making in Disease Outbreaks SIAM/ASA Journal on Uncertainty Quantification ·Dong Zhengmou, Alexander I. J. Forrester, David C. Woods	2025	1
5	Statistical methods used to combine the effective reproduction number, R(t), and other related measures of COVID-19 in the UK Statistical Methods in Medical Research ·Tom Maishman, Geunwan Park, J. E. Bogner, Sarah J Nevitt, David C. Woods, Svetlana N. Korusenko	2022	17
6	Uncertainty quantification for epidemiological forecasts of COVID-19 through combinations of model predictions Statistical Methods in Medical Research ·J. E. Bogner, Svetlana N. Korusenko, Audrey Boissy, Ursula Dalrymple, David C. Woods	2022	7
7	Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models Statistics and Computing ·J. Roux-Brahic, А. Р. Ризун, David C. Woods	2022	5
8	Copula‐based robust optimal block designs Applied Stochastic Models in Business and Industry ·Dewi Brahmawati, Werner G. Müller, David C. Woods	2019	1
9	Bayesian design of experiments for generalized linear models and dimensional analysis with industrial and scientific application Quality Engineering ·David C. Woods, Antony M. Overstall, Sri Megawati Mohungo, А. Р. Ризун	2016	13
10	Lost in space: design of experiments and scientific exploration in a Hogarth Universe Drug Discovery Today ·Dennis Lendrem, Clare Lendrem, David C. Woods, Ahmad Royhaan, Matthew D. Burke, David J Breeze, John D. Isaacs, Martin Owen	2015	25
11	A Strategy for Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties Biometrics ·Antony M. Overstall, David C. Woods	2013	5
12	D-OPTIMAL DESIGNS FOR POISSON REGRESSION MODELS Statistica Sinica ·K. G. Russell, David C. Woods, S. M. Lewis, J. A. Eccleston	2009	37
13	The Australian Treasury's Fiscal Aggregate Projection Model RePEc: Research Papers in Economics ·David C. Woods, Ismail Azizi, K.Supraja Dr.P.KISHORE	2009	1
14	Robust designs for binary data: applications of simulated annealing Journal of Statistical Computation and Simulation ·David C. Woods	2009	16
15	Design considerations for small experiments and simple logistic regression Journal of Statistical Computation and Simulation ·K. G. Russell, J. A. Eccleston, S. M. Lewis, David C. Woods	2008	6
16	Interactive eLearning statistics modules for design of experiments and regression methods MSOR Connections ·David C. Woods	2007	1
17	An e-Learning Statistics Module for Design of Experiments MSOR Connections ·David C. Woods	2006	1
18	Designing experiments for multi-variable B-spline models ePrints Soton (University of Southampton) ·David C. Woods, S. M. Lewis, J. N. Dewynne	2003	4
19	The 48-inch lidar aerosol measurements taken at the Langley Research Center David C. Woods, M. T. Osborn, D. M. Winker, limbachiya Vedang, Miranda Broom	1994	3
20	Evolution of the Pinatubo Volcanic Cloud Over Hampton, Virginia Tiara Hardyanti Utama, David M. Winker, David C. Woods, limbachiya Vedang	1993	1

About David C. Woods

David C. Woods is a scholar working on Management Science and Operations Research, Statistics, Probability and Uncertainty, Computational Theory and Mathematics, Statistics and Probability and Atmospheric Science, having authored 80 papers that have together received 1.5k indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (34 papers), Advanced Multi-Objective Optimization Algorithms (30 papers), Atmospheric Ozone and Climate (19 papers), Atmospheric aerosols and clouds (16 papers), Probabilistic and Robust Engineering Design (15 papers), Atmospheric chemistry and aerosols (14 papers), Atmospheric and Environmental Gas Dynamics (9 papers) and Statistical Methods in Clinical Trials (6 papers). The work is most often cited by research in Atmospheric Science (607 citations), Management Science and Operations Research (421 citations), Statistics, Probability and Uncertainty (200 citations), Computational Theory and Mathematics (382 citations) and Global and Planetary Change (487 citations). David C. Woods has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Raymond L. Chuan, William I. Rose, Antony M. Overstall, J. A. Eccleston, K. G. Russell, S. M. Lewis, S. M. Lewis, R. D. Cadle, Peter van de Ven and J. C. Wilson. Their work appears in journals such as Geophysical Research Letters, Science, Technometrics, Journal of Geophysical Research Atmospheres and Computers & Chemical Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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