James McGree

3.4k total citations
119 papers, 2.1k citations indexed

About

James McGree is a scholar working on Environmental Engineering, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, James McGree has authored 119 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Environmental Engineering, 21 papers in Statistics and Probability and 18 papers in Management Science and Operations Research. Recurrent topics in James McGree's work include Urban Stormwater Management Solutions (20 papers), Optimal Experimental Design Methods (18 papers) and Advanced Multi-Objective Optimization Algorithms (14 papers). James McGree is often cited by papers focused on Urban Stormwater Management Solutions (20 papers), Optimal Experimental Design Methods (18 papers) and Advanced Multi-Objective Optimization Algorithms (14 papers). James McGree collaborates with scholars based in Australia, United States and China. James McGree's co-authors include Ashantha Goonetilleke, Prasanna Egodawatta, Christopher Drovandi, Buddhi Wijesiri, A. N. Pettitt, An Liu, Yukun Ma, Melody A. de Laat, Martin N. Sillence and Elizabeth Ryan and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and Water Research.

In The Last Decade

James McGree

113 papers receiving 2.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
James McGree Australia 25 541 364 298 271 226 119 2.1k
Jessica Davies United Kingdom 25 369 0.7× 509 1.4× 430 1.4× 90 0.3× 54 0.2× 88 2.2k
William F. Christensen United States 22 488 0.9× 56 0.2× 153 0.5× 205 0.8× 38 0.2× 79 2.2k
Karen Chan Italy 8 578 1.1× 331 0.9× 546 1.8× 78 0.3× 238 1.1× 9 3.0k
Arash Azari Iran 18 278 0.5× 315 0.9× 211 0.7× 50 0.2× 18 0.1× 36 939
Ruiping Li China 27 251 0.5× 390 1.1× 206 0.7× 503 1.9× 27 0.1× 118 2.3k
Stefano Marsili-Libelli Italy 28 718 1.3× 1.1k 3.1× 619 2.1× 634 2.3× 127 0.6× 81 3.2k
Hongbo Zhang China 26 631 1.2× 956 2.6× 571 1.9× 79 0.3× 38 0.2× 179 2.9k
Orhan Dengız Türkiye 26 772 1.4× 168 0.5× 371 1.2× 211 0.8× 208 0.9× 256 2.8k
Xiaoxi Wang China 21 177 0.3× 122 0.3× 146 0.5× 87 0.3× 37 0.2× 114 1.9k
Wenzhi Zeng China 30 1.1k 2.0× 480 1.3× 730 2.4× 61 0.2× 59 0.3× 117 3.3k

Countries citing papers authored by James McGree

Since Specialization
Citations

This map shows the geographic impact of James McGree'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 James McGree with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James McGree more than expected).

Fields of papers citing papers by James McGree

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James McGree. 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 James McGree. The network helps show where James McGree may publish in the future.

Co-authorship network of co-authors of James McGree

This figure shows the co-authorship network connecting the top 25 collaborators of James McGree. A scholar is included among the top collaborators of James McGree based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James McGree. James McGree is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rallapalli, Srinivas, et al.. (2025). Developing strategic and staging optimization pathways for urban flood damage mitigation. Journal of Hydrology. 659. 133315–133315.
2.
Cure, Katherine, Diego R. Barneche, Martial Depczynski, et al.. (2024). Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making. AMBIO. 53(5). 746–763. 2 indexed citations
3.
4.
McGree, James, et al.. (2023). Managing surgical waiting lists through dynamic priority scoring. Health Care Management Science. 26(3). 533–557. 6 indexed citations
5.
Müller, Werner G., et al.. (2023). Bayesian design for minimizing prediction uncertainty in bivariate spatial responses with applications to air quality monitoring. Biometrical Journal. 65(4). e2100386–e2100386. 4 indexed citations
6.
7.
Meier, Alexandra, James McGree, J.M.H. Preuss, et al.. (2021). The application of a new laminitis scoring method to model the rate and pattern of improvement from equine endocrinopathic laminitis in a clinical setting. BMC Veterinary Research. 17(1). 16–16. 3 indexed citations
8.
Overstall, Antony M., et al.. (2020). Bayesian adaptive N-of-1 trials for estimating population and individual treatment effects. QUT ePrints (Queensland University of Technology). 6 indexed citations
9.
Leigh, Catherine, Rob J. Hyndman, Sevvandi Kandanaarachchi, et al.. (2019). A framework for automated anomaly detection in high frequency water-quality data from in situ sensors. The Science of The Total Environment. 664. 885–898. 83 indexed citations
10.
Ma, Yukun, Kaveh Deilami, Prasanna Egodawatta, et al.. (2019). Creating a hierarchy of hazard control for urban stormwater management. Environmental Pollution. 255(Pt 1). 113217–113217. 12 indexed citations
11.
Fripp, Jürgen, et al.. (2017). Comparisons of neurodegeneration over time between healthy ageing and Alzheimer's disease cohorts via Bayesian inference. BMJ Open. 7(2). e012174–e012174. 9 indexed citations
12.
Meier, Alexandra, Melody A. de Laat, Dania Reiche, et al.. (2017). The oral glucose test predicts laminitis risk in ponies fed a diet high in nonstructural carbohydrates. Domestic Animal Endocrinology. 63. 1–9. 67 indexed citations
13.
Drovandi, Christopher, Chris Holmes, James McGree, et al.. (2017). Principles of Experimental Design for Big Data Analysis. Statistical Science. 32(3). 385–404. 27 indexed citations
14.
Ma, Yukun, Prasanna Egodawatta, James McGree, An Liu, & Ashantha Goonetilleke. (2016). Human health risk assessment of heavy metals in urban stormwater. The Science of The Total Environment. 557-558. 764–772. 163 indexed citations
15.
McGree, James, et al.. (2015). Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson's disease. International Journal of Applied Mathematics & Statistics. 53(6). 145–151. 4 indexed citations
16.
Watson, Kalinda, María José Farré, James Birt, James McGree, & Nicole Knight. (2015). Predictive models for water sources with high susceptibility for bromine-containing disinfection by-product formation: Implications for water treatment. e-publications@bond (Bond University).
17.
Egodawatta, Prasanna, James McGree, Buddhi Wijesiri, & Ashantha Goonetilleke. (2014). Compatibility of stormwater treatment performance data between different geographical areas. QUT ePrints (Queensland University of Technology). 41(5). 53. 1 indexed citations
18.
McGree, James, Christopher Drovandi, & A. N. Pettitt. (2012). A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models. Science & Engineering Faculty. 33(3). 256–8. 3 indexed citations
19.
McGree, James, Christopher Drovandi, & A. N. Pettitt. (2012). A sequential Monte Carlo approach to derive sampling times and windows for population pharmacokinetic studies. Journal of Pharmacokinetics and Pharmacodynamics. 39(5). 519–526. 7 indexed citations
20.
McGree, James, Stephen B. Duffull, J. A. Eccleston, & Leigh C. Ward. (2007). Optimal designs for studying bioimpedance. Physiological Measurement. 28(12). 1465–1483. 6 indexed citations

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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