Michael A. Lones

1.7k total citations
63 papers, 893 citations indexed

About

Michael A. Lones is a scholar working on Artificial Intelligence, Molecular Biology and Neurology. According to data from OpenAlex, Michael A. Lones has authored 63 papers receiving a total of 893 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 23 papers in Molecular Biology and 14 papers in Neurology. Recurrent topics in Michael A. Lones's work include Evolutionary Algorithms and Applications (20 papers), Gene Regulatory Network Analysis (14 papers) and Parkinson's Disease Mechanisms and Treatments (13 papers). Michael A. Lones is often cited by papers focused on Evolutionary Algorithms and Applications (20 papers), Gene Regulatory Network Analysis (14 papers) and Parkinson's Disease Mechanisms and Treatments (13 papers). Michael A. Lones collaborates with scholars based in United Kingdom, Malaysia and United States. Michael A. Lones's co-authors include Stephen L. Smith, Andy M. Tyrrell, A.M. Tyrrell, Jane Alty, Stuart Lacy, Mike Just, Jeremy Cosgrove, Stuart W. Jamieson, Mary Elizabeth Pownall and Susan Stepney and has published in prestigious journals such as SHILAP Revista de lepidopterología, Science Advances and IEEE Access.

In The Last Decade

Michael A. Lones

58 papers receiving 859 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael A. Lones United Kingdom 17 353 207 154 90 90 63 893
Zhengxia Wang China 16 162 0.5× 124 0.6× 25 0.2× 78 0.9× 32 0.4× 56 793
Na Zou United States 17 376 1.1× 53 0.3× 18 0.1× 55 0.6× 11 0.1× 70 1.0k
Gustavo Henrique de Rosa Brazil 12 253 0.7× 33 0.2× 223 1.4× 68 0.8× 5 0.1× 37 816
Magnus Johnsson Sweden 15 259 0.7× 26 0.1× 37 0.2× 42 0.5× 27 0.3× 46 717
Saeeda Naz Pakistan 23 711 2.0× 25 0.1× 96 0.6× 9 0.1× 43 0.5× 60 2.1k
V́ıctor González-Castro Spain 20 311 0.9× 35 0.2× 44 0.3× 93 1.0× 9 0.1× 59 1.2k
Nini Rao China 22 129 0.4× 761 3.7× 27 0.2× 14 0.2× 12 0.1× 86 1.7k
Yinan Kong Australia 18 751 2.1× 43 0.2× 11 0.1× 59 0.7× 25 0.3× 88 1.5k
Sajid Iqbal Pakistan 18 573 1.6× 53 0.3× 14 0.1× 26 0.3× 44 0.5× 48 1.5k
Vinh‐Thong Ta France 12 69 0.2× 33 0.2× 45 0.3× 36 0.4× 18 0.2× 28 606

Countries citing papers authored by Michael A. Lones

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Lones

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Lones. 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 Michael A. Lones. The network helps show where Michael A. Lones may publish in the future.

Co-authorship network of co-authors of Michael A. Lones

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Lones. A scholar is included among the top collaborators of Michael A. Lones 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 Michael A. Lones. Michael A. Lones 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.
Just, Mike, et al.. (2025). IoTGeM: Generalizable models for behaviour-based IoT attack detection. Computer Networks. 270. 111550–111550.
2.
Just, Mike, et al.. (2025). GeMID: Generalizable models for IoT device identification. Internet of Things. 34. 101806–101806.
3.
Just, Mike, et al.. (2025). Individual Packet Features are a Risk to Model Generalization in ML-Based Intrusion Detection. IEEE Networking Letters. 7(1). 66–70. 3 indexed citations
4.
Lones, Michael A., et al.. (2025). Navigating the Landscape of Automated Feedback Generation Techniques for Programming Exercises. ACM Transactions on Computing Education. 25(4). 1–29.
5.
Kapoor, Sayash, Christopher A. Bail, Odd Erik Gundersen, et al.. (2024). REFORMS: Consensus-based Recommendations for Machine-learning-based Science. Science Advances. 10(18). eadk3452–eadk3452. 27 indexed citations
6.
Lones, Michael A.. (2024). Avoiding common machine learning pitfalls. Patterns. 5(10). 101046–101046. 28 indexed citations
7.
8.
Almeida, Leandro de, et al.. (2022). Measuring the impact of nonpharmaceutical interventions on the SARS-CoV-2 pandemic at a city level: An agent-based computational modelling study of the City of Natal. SHILAP Revista de lepidopterología. 2(10). e0000540–e0000540. 1 indexed citations
9.
Lones, Michael A., et al.. (2021). Parkinson’s disease diagnosis using convolutional neural networks and figure-copying tasks. Neural Computing and Applications. 34(2). 1433–1453. 47 indexed citations
10.
Lones, Michael A., et al.. (2021). Evaluation of recurrent neural network models for Parkinson’s disease classification using drawing data. 1 indexed citations
11.
Cosgrove, Jeremy, Mark R. Hinder, Rebecca J. St George, et al.. (2021). Significant cognitive decline in Parkinson's disease exacerbates the reliance on visual feedback during upper limb reaches. Neuropsychologia. 157. 107885–107885. 3 indexed citations
12.
Elias, Leonardo Abdala, et al.. (2021). A Data-Driven Biophysical Computational Model of Parkinson’s Disease Based on Marmoset Monkeys. IEEE Access. 9. 122548–122567. 4 indexed citations
13.
Gao, Chao, Stephen L. Smith, Michael A. Lones, et al.. (2018). Objective assessment of bradykinesia in Parkinson’s disease using evolutionary algorithms: clinical validation. Translational Neurodegeneration. 7(1). 18–18. 34 indexed citations
14.
Turner, Alexander P., Andy M. Tyrrell, Martin A. Trefzer, & Michael A. Lones. (2018). Evolutionary acquisition of complex traits in artificial epigenetic networks. Biosystems. 176. 17–26.
15.
Lones, Michael A., Jane Alty, Jeremy Cosgrove, et al.. (2017). A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson’s Dyskinesia. Journal of Medical Systems. 41(11). 176–176. 17 indexed citations
16.
Lones, Michael A., Jane Alty, Jeremy Cosgrove, Stuart W. Jamieson, & Stephen L. Smith. (2017). Going through directional changes. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1365–1371. 2 indexed citations
17.
Turner, Alexander P., Michael A. Lones, Martin A. Trefzer, et al.. (2016). Using epigenetic networks for the analysis of movement associated with levodopa therapy for Parkinson's disease. Biosystems. 146. 35–42. 3 indexed citations
18.
Lones, Michael A., et al.. (2013). Characterising neurological time series data using biologically motivated networks of coupled discrete maps. Biosystems. 112(2). 94–101. 10 indexed citations
19.
Harris, Andrew T., Stephen L. Smith, Michael A. Lones, et al.. (2009). Potential for Raman spectroscopy to provide cancer screening using a peripheral blood sample. Head & Neck Oncology. 1(1). 34–34. 58 indexed citations
20.
Smith, Stephen L. & Michael A. Lones. (2009). Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability. 3449. 1072–1078. 5 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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