Richard Everson

9.5k total citations · 4 hit papers
129 papers, 5.4k citations indexed

About

Richard Everson is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Richard Everson has authored 129 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 27 papers in Computational Theory and Mathematics and 12 papers in Computational Mechanics. Recurrent topics in Richard Everson's work include Advanced Multi-Objective Optimization Algorithms (23 papers), Neural Networks and Applications (11 papers) and Blind Source Separation Techniques (9 papers). Richard Everson is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (23 papers), Neural Networks and Applications (11 papers) and Blind Source Separation Techniques (9 papers). Richard Everson collaborates with scholars based in United Kingdom, United States and China. Richard Everson's co-authors include Liang Hao, L. Sirovich, Jonathan E. Fieldsend, G. Strano, K. Evans, Chunze Yan, Ahmed Hussein, Stephen Roberts, Yulan He and Chenghua Lin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and SHILAP Revista de lepidopterología.

In The Last Decade

Richard Everson

123 papers receiving 5.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Surface roughness analysis, modelling and prediction in selective laser melting

2012 694 citations G. Strano, Liang Hao et al. profile →
Karhunen–Loève procedure for gappy data

1995 579 citations Richard Everson et al. profile →
Finite element simulation of the temperature and stress fields in single layers built without-support in selective laser melting

2013 562 citations Liang Hao, Richard Everson et al. profile →
A new approach to the design and optimisation of support structures in additive manufacturing

2012 302 citations G. Strano, Liang Hao et al. The International Journal of Advanced Manufacturing Technology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Richard Everson United Kingdom	34	1.8k	1.5k	1.2k	675	615	129	5.4k
Moritz Diehl Germany	49	1.1k 0.6×	1.8k 1.2×	692 0.6×	687 1.0×	264 0.4×	455	14.4k
Andreas Wächter United States	20	590 0.3×	735 0.5×	547 0.5×	773 1.1×	181 0.3×	57	9.4k
Jin Jiang Canada	50	1.5k 0.8×	638 0.4×	785 0.7×	281 0.4×	95 0.2×	343	11.9k
Weidong Zhang China	55	1.1k 0.6×	427 0.3×	1.1k 0.9×	226 0.3×	574 0.9×	915	13.0k
Jian‐Qiao Sun United States	35	1.5k 0.8×	373 0.3×	488 0.4×	263 0.4×	753 1.2×	248	6.1k
Jianbin Qiu China	74	1.1k 0.6×	565 0.4×	2.4k 2.1×	171 0.3×	940 1.5×	291	15.6k
Lixin Wang China	28	570 0.3×	560 0.4×	2.9k 2.5×	248 0.4×	339 0.6×	304	8.0k
Hui Zhang China	53	2.0k 1.1×	3.2k 2.2×	1.0k 0.9×	153 0.2×	172 0.3×	383	10.2k
Tao Zhang China	48	2.4k 1.3×	519 0.4×	1.6k 1.4×	316 0.5×	100 0.2×	894	11.4k
C.J. Harris United Kingdom	45	818 0.4×	413 0.3×	2.9k 2.5×	294 0.4×	169 0.3×	362	8.1k

Countries citing papers authored by Richard Everson

Since Specialization

Citations

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

Fields of papers citing papers by Richard Everson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Everson

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Everson. A scholar is included among the top collaborators of Richard Everson 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 Richard Everson. Richard Everson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ath, George De, et al.. (2026). Human-In-The-Loop Testing of AI Agents for Air Traffic Control With a Regulated Assessment Framework. ArXiv.org.

Ath, George De, et al.. (2025). A sector-specific probabilistic approach for 4D aircraft trajectory generation. Transportation Research Part C Emerging Technologies. 179. 105291–105291.

Everson, Richard, et al.. (2025). Water level estimation in sewage pipes using texture-based methods and machine learning algorithms. Water Science & Technology. 91(6). 746–756. 1 indexed citations

HENDERSON, E, et al.. (2025). Air Traffic Controller Task Demand via Graph Neural Networks: An Interpretable Approach to Airspace Complexity. ArXiv.org. 1 indexed citations

Thomas, M., et al.. (2023). A probabilistic model for aircraft in climb using monotonic functional Gaussian process emulators. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 479(2271). 4 indexed citations

Everson, Richard, et al.. (2022). Optimising Diversity in Classifier Ensembles. SN Computer Science. 3(3).

José-García, Adán, et al.. (2022). C3-IoC: A Career Guidance System for Assessing Student Skills using Machine Learning and Network Visualisation. International Journal of Artificial Intelligence in Education. 33(4). 1092–1119. 13 indexed citations

Allen, Michael, Charlotte James, Julia Frost, et al.. (2022). Using simulation and machine learning to maximise the benefit of intravenous thrombolysis in acute stroke in England and Wales: the SAMueL modelling and qualitative study. SHILAP Revista de lepidopterología. 10(31). 1–148. 5 indexed citations

Rahat, Alma, et al.. (2019). Automated shape optimisation of a plane asymmetric diffuser using combined Computational Fluid Dynamic simulations and multi-objective Bayesian methodology. International journal of computational fluid dynamics. 33(6-7). 256–271. 6 indexed citations

10.

Meakin, Judith R., Ryan M. Ames, J. Charles G. Jeynes, et al.. (2019). The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation. PLoS ONE. 14(10). e0222523–e0222523. 4 indexed citations

11.

Littlejohn, George R., Jessica Mansfield, Jacqueline Christmas, et al.. (2014). An update: improvements in imaging perfluorocarbon-mounted plant leaves with implications for studies of plant pathology, physiology, development and cell biology. Frontiers in Plant Science. 5. 140–140. 52 indexed citations

12.

Powell, Isaac J., Greg Dyson, Susan Land, et al.. (2013). Genes Associated with Prostate Cancer Are Differentially Expressed in African American and European American Men. Cancer Epidemiology Biomarkers & Prevention. 22(5). 891–897. 127 indexed citations

13.

Strano, G., Liang Hao, Richard Everson, & K. Evans. (2012). A new approach to the design and optimisation of support structures in additive manufacturing. The International Journal of Advanced Manufacturing Technology. 66(9-12). 1247–1254. 302 indexed citations breakdown →

14.

Lin, Chenghua, Yulan He, & Richard Everson. (2011). Sentence Subjectivity Detection with Weakly-Supervised Learning. Open Research Online (The Open University). 1153–1161. 26 indexed citations

15.

Lin, Chenghua, Yulan He, & Richard Everson. (2010). A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection. Open Research Online (The Open University). 144–152. 29 indexed citations

16.

Schetinin, Vitaly, Jonathan E. Fieldsend, Derek Partridge, et al.. (2007). Confident Interpretation of Bayesian Decision Tree Ensembles for Clinical Applications. IEEE Transactions on Information Technology in Biomedicine. 11(3). 312–319. 42 indexed citations

17.

Everson, Richard, et al.. (2002). Controlling Genetic Algorithms With Reinforcement Learning. Genetic and Evolutionary Computation Conference. 692–692. 27 indexed citations

18.

Roberts, Stephen, Richard Everson, & Iead Rezek. (2000). Maximum certainty data partitioning. Pattern Recognition. 33(5). 833–839. 49 indexed citations

19.

Roberts, Stephen, et al.. (2000). Automated assessment of vigilance usingcommittees of radial basis function analysers. IEE Proceedings - Science Measurement and Technology. 147(6). 333–338. 23 indexed citations

20.

Everson, Richard & Katepalli R. Sreenivasan. (1992). Accumulation rates of spiral-like structures in fluid flows. Proceedings of the Royal Society of London Series A Mathematical and Physical Sciences. 437(1900). 391–401. 10 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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