Christopher Drovandi

3.6k total citations
133 papers, 1.8k citations indexed

About

Christopher Drovandi is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Christopher Drovandi has authored 133 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Statistics and Probability, 45 papers in Artificial Intelligence and 18 papers in Management Science and Operations Research. Recurrent topics in Christopher Drovandi's work include Statistical Methods and Bayesian Inference (37 papers), Markov Chains and Monte Carlo Methods (33 papers) and Bayesian Methods and Mixture Models (21 papers). Christopher Drovandi is often cited by papers focused on Statistical Methods and Bayesian Inference (37 papers), Markov Chains and Monte Carlo Methods (33 papers) and Bayesian Methods and Mixture Models (21 papers). Christopher Drovandi collaborates with scholars based in Australia, United Kingdom and Singapore. Christopher Drovandi's co-authors include A. N. Pettitt, James McGree, Elizabeth Ryan, Kerrie Mengersen, David J. Nott, Anthony Lee, David T. Frazier, Brodie Lawson, Kevin Burrage and Christian P. Robert and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Technometrics.

In The Last Decade

Christopher Drovandi

128 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher Drovandi Australia 20 600 539 265 260 186 133 1.8k
S. Rao Jammalamadaka United States 22 1.1k 1.8× 674 1.3× 235 0.9× 176 0.7× 77 0.4× 118 2.7k
Jane-Ling Wang United States 28 2.3k 3.8× 986 1.8× 263 1.0× 211 0.8× 70 0.4× 97 4.3k
Leslie M. Moore United States 12 244 0.4× 250 0.5× 545 2.1× 618 2.4× 729 3.9× 28 2.5k
M. C. Jones United Kingdom 22 724 1.2× 440 0.8× 137 0.5× 140 0.5× 53 0.3× 73 2.4k
Andrew A. Neath United States 11 550 0.9× 392 0.7× 151 0.6× 146 0.6× 40 0.2× 31 2.3k
David M. Giltinan United States 19 984 1.6× 266 0.5× 154 0.6× 269 1.0× 91 0.5× 29 2.7k
Chong Gu United States 23 1.0k 1.7× 442 0.8× 166 0.6× 141 0.5× 76 0.4× 48 2.1k
Berwin A. Turlach Australia 24 702 1.2× 430 0.8× 95 0.4× 152 0.6× 105 0.6× 84 2.2k
Merlise A. Clyde United States 23 992 1.7× 657 1.2× 168 0.6× 258 1.0× 121 0.7× 53 2.7k
Richard R. Picard United States 10 198 0.3× 174 0.3× 106 0.4× 119 0.5× 63 0.3× 30 1.8k

Countries citing papers authored by Christopher Drovandi

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Drovandi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Drovandi

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Drovandi. A scholar is included among the top collaborators of Christopher Drovandi 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 Christopher Drovandi. Christopher Drovandi 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.
Frazier, David T., David J. Nott, & Christopher Drovandi. (2024). Synthetic Likelihood in Misspecified Models. Journal of the American Statistical Association. 120(550). 884–895.
2.
Wang, Xiaoyu, et al.. (2024). Calibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation. Journal of Mathematical Biology. 88(3). 28–28. 4 indexed citations
3.
Warne, David J., Oliver J. Maclaren, Elliot J. Carr, Matthew J. Simpson, & Christopher Drovandi. (2023). Generalised likelihood profiles for models with intractable likelihoods. Statistics and Computing. 34(1). 5 indexed citations
4.
Lawson, Brodie, Christopher Drovandi, Kevin Burrage, et al.. (2022). Analysis of sloppiness in model simulations: unveiling parameter uncertainty when mathematical models are fitted to data. arXiv (Cornell University). 27 indexed citations
5.
Price, David J., et al.. (2022). Optimal Bayesian design for model discrimination via classification. Statistics and Computing. 32(2). 25–25. 1 indexed citations
6.
Drovandi, Christopher, et al.. (2022). Computationally efficient mechanism discovery for cell invasion with uncertainty quantification. PLoS Computational Biology. 18(11). e1010599–e1010599. 4 indexed citations
7.
Browning, Alexander P., Christopher Drovandi, Ian Turner, Adrianne L. Jenner, & Matthew J. Simpson. (2022). Efficient inference and identifiability analysis for differential equation models with random parameters. PLoS Computational Biology. 18(11). e1010734–e1010734. 6 indexed citations
8.
Browning, Alexander P., Niloufar Ansari, Christopher Drovandi, et al.. (2022). Identifying cell-to-cell variability in internalization using flow cytometry. Journal of The Royal Society Interface. 19(190). 20220019–20220019. 5 indexed citations
9.
Minett, Geoffrey M., Ian B. Stewart, Stewart G. Trost, et al.. (2022). Evidence that heat acclimation training may alter sleep and incidental activity. European Journal of Sport Science. 23(8). 1731–1740. 2 indexed citations
10.
Stewart, Ian B., et al.. (2021). Analysing the predictive capacity and dose-response of wellness in load monitoring. Journal of Sports Sciences. 39(12). 1339–1347. 10 indexed citations
11.
Sisson, Scott A., et al.. (2021). Efficient Bayesian Synthetic Likelihood With Whitening Transformations. Journal of Computational and Graphical Statistics. 31(1). 50–63. 9 indexed citations
12.
Simpson, Matthew J., et al.. (2021). Estimating parameters of a stochastic cell invasion model with fluorescent cell cycle labelling using approximate Bayesian computation. Journal of The Royal Society Interface. 18(182). 20210362–20210362. 9 indexed citations
13.
Flegg, Jennifer A., et al.. (2020). A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models. Royal Society Open Science. 7(3). 191315–191315. 11 indexed citations
14.
Borg, David N., et al.. (2020). The effect of access to a designated interdisciplinary post-acute rehabilitation service on participant outcomes after brain injury. Brain Injury. 34(10). 1358–1366. 10 indexed citations
15.
MacNeil, M. Aaron, Camille Mellin, Samuel A. Matthews, et al.. (2019). Water quality mediates resilience on the Great Barrier Reef. Nature Ecology & Evolution. 3(4). 620–627. 141 indexed citations
16.
Drovandi, Christopher, David J. Nott, & Dan Pagendam. (2017). New Insights into History Matching via Sequential Monte Carlo. QUT ePrints (Queensland University of Technology). 1 indexed citations
17.
Drovandi, Christopher, et al.. (2016). Exact and approximate Bayesian inference for low count time series models with intractable likelihoods. Bayesian Analysis. 1 indexed citations
18.
Drovandi, Christopher. (2014). Pseudo-marginal algorithms with multiple CPUs. QUT ePrints (Queensland University of Technology). 2 indexed citations
19.
Drovandi, Christopher. (2012). Bayesian algorithms with applications. Science & Engineering Faculty. 1 indexed citations
20.
Drovandi, Christopher & A. N. Pettitt. (2012). Discussion of : constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation. Journal of the Royal Statistical Society Series B (Statistical Methodology). 35(6). 914–21. 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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