Benjamin D. Evans

990 total citations
25 papers, 426 citations indexed

About

Benjamin D. Evans is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Benjamin D. Evans has authored 25 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 7 papers in Cellular and Molecular Neuroscience and 7 papers in Artificial Intelligence. Recurrent topics in Benjamin D. Evans's work include Neural dynamics and brain function (11 papers), Advanced Memory and Neural Computing (6 papers) and Photoreceptor and optogenetics research (5 papers). Benjamin D. Evans is often cited by papers focused on Neural dynamics and brain function (11 papers), Advanced Memory and Neural Computing (6 papers) and Photoreceptor and optogenetics research (5 papers). Benjamin D. Evans collaborates with scholars based in United Kingdom, United States and Italy. Benjamin D. Evans's co-authors include Konstantin Nikolić, Jeffrey S. Bowers, Gaurav Malhotra, E. Coiras, Müntzer Mughal, Sung‐Tong Chin, George B. Hanna, Stefan Antonowicz, Jesper Lagergren and Sheraz R. Markar and has published in prestigious journals such as Nature Communications, PLoS ONE and Development.

In The Last Decade

Benjamin D. Evans

22 papers receiving 413 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benjamin D. Evans United Kingdom 11 131 85 82 57 55 25 426
Ruimin Wang China 11 83 0.6× 60 0.7× 140 1.7× 16 0.3× 39 0.7× 42 415
Chia-Wei Sun Taiwan 9 192 1.5× 126 1.5× 22 0.3× 14 0.2× 109 2.0× 15 444
Gordon B. Scarth Canada 9 102 0.8× 51 0.6× 77 0.9× 28 0.5× 7 0.1× 15 406
Sharmishtaa Seshamani United States 10 43 0.3× 81 1.0× 150 1.8× 50 0.9× 62 1.1× 24 733
Д. С. Лебедев Russia 15 26 0.2× 41 0.5× 137 1.7× 41 0.7× 34 0.6× 155 1.2k
Nhi Ngo Vietnam 16 32 0.2× 74 0.9× 193 2.4× 27 0.5× 10 0.2× 34 672
Elvan Ceyhan Türkiye 12 100 0.8× 62 0.7× 36 0.4× 40 0.7× 14 0.3× 47 405
Robert E. Yantorno United States 14 37 0.3× 30 0.4× 203 2.5× 172 3.0× 98 1.8× 46 646
Kensuke Arai Japan 11 311 2.4× 59 0.7× 51 0.6× 26 0.5× 88 1.6× 35 591
Kay C. Wiese Canada 14 40 0.3× 42 0.5× 396 4.8× 65 1.1× 6 0.1× 56 664

Countries citing papers authored by Benjamin D. Evans

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin D. Evans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin D. Evans. 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 Benjamin D. Evans. The network helps show where Benjamin D. Evans may publish in the future.

Co-authorship network of co-authors of Benjamin D. Evans

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin D. Evans. A scholar is included among the top collaborators of Benjamin D. Evans 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 Benjamin D. Evans. Benjamin D. Evans 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.
Evans, Benjamin D., et al.. (2024). Adapting to time: Why nature may have evolved a diverse set of neurons. PLoS Computational Biology. 20(12). e1012673–e1012673. 2 indexed citations
2.
Furley, David J., Elizabeth Manning, Matthew Towers, et al.. (2023). Accurate staging of chick embryonic tissues via deep learning of salient features. Development. 150(22). 5 indexed citations
3.
Malhotra, Gaurav, et al.. (2023). The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data. Neural Networks. 161. 515–524. 3 indexed citations
4.
Bowers, Jeffrey S., Gaurav Malhotra, Marin Dujmović, et al.. (2023). Clarifying status of DNNs as models of human vision. Behavioral and Brain Sciences. 46. e415–e415. 4 indexed citations
5.
Bowers, Jeffrey S., Gaurav Malhotra, Marin Dujmović, et al.. (2022). Deep problems with neural network models of human vision. Behavioral and Brain Sciences. 46. e385–e385. 68 indexed citations
6.
Evans, Benjamin D., Piotr Słowiński, Andrew T. Hattersley, et al.. (2021). Estimating disease prevalence in large datasets using genetic risk scores. Nature Communications. 12(1). 6441–6441. 5 indexed citations
7.
Brunt, Lucy, Gediminas Greicius, Sally Rogers, et al.. (2021). Vangl2 promotes the formation of long cytonemes to enable distant Wnt/β-catenin signaling. Nature Communications. 12(1). 2058–2058. 49 indexed citations
8.
Evans, Benjamin D., Gaurav Malhotra, & Jeffrey S. Bowers. (2021). Biological convolutions improve DNN robustness to noise and generalisation. Neural Networks. 148. 96–110. 15 indexed citations
9.
Malhotra, Gaurav, Benjamin D. Evans, & Jeffrey S. Bowers. (2020). Hiding a plane with a pixel: examining shape-bias in CNNs and the benefit of building in biological constraints. Vision Research. 174. 57–68. 18 indexed citations
10.
Malhotra, Gaurav, et al.. (2020). Adding Biological Constraints to Deep Neural Networks Reduces their Capacity to Learn Unstructured Data. Cognitive Science. 2358–2364. 2 indexed citations
11.
Hernandez, Bernard, Pau Herrero, Timothy M. Rawson, et al.. (2017). Supervised learning for infection risk inference using pathology data. BMC Medical Informatics and Decision Making. 17(1). 168–168. 34 indexed citations
12.
Evans, Benjamin D., Sarah Jarvis, Simon R. Schultz, & Konstantin Nikolić. (2016). PyRhO: A Multiscale Optogenetics Simulation Platform. Frontiers in Neuroinformatics. 10. 8–8. 21 indexed citations
13.
Evans, Benjamin D., et al.. (2015). Computational modeling of the neural representation of object shape in the primate ventral visual system. Frontiers in Computational Neuroscience. 9. 100–100. 5 indexed citations
14.
Evans, Benjamin D., et al.. (2015). Live demonstration: A low-power neuromorphic system for retinal implants and sensory substitution. Spiral (Imperial College London). 1–1. 3 indexed citations
15.
Evans, Benjamin D. & Simon M. Stringer. (2014). STDP in lateral connections creates category-based perceptual cycles for invariance learning with multiple stimuli. Biological Cybernetics. 109(2). 215–239. 1 indexed citations
16.
Evans, Benjamin D. & Simon M. Stringer. (2013). How Lateral Connections and Spiking Dynamics May Separate Multiple Objects Moving Together. PLoS ONE. 8(8). e69952–e69952. 6 indexed citations
17.
Evans, Benjamin D., et al.. (2013). A Self-Organizing Model of the Visual Development of Hand-Centred Representations. PLoS ONE. 8(6). e66272–e66272. 4 indexed citations
18.
Evans, Benjamin D.. (2012). Transformation-invariant visual representations in self-organizing spiking neural networks. Frontiers in Computational Neuroscience. 6. 46–46. 19 indexed citations
19.
Groen, J., et al.. (2010). Model-based sea mine classification with synthetic aperture sonar. IET Radar Sonar & Navigation. 4(1). 62–73. 19 indexed citations
20.
Coiras, E., et al.. (2009). Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction. EURASIP Journal on Advances in Signal Processing. 2009(1). 17 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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