Raghavendra Selvan

1.2k total citations
32 papers, 246 citations indexed

About

Raghavendra Selvan is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Raghavendra Selvan has authored 32 papers receiving a total of 246 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Cognitive Neuroscience and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Raghavendra Selvan's work include Topic Modeling (3 papers), Amyotrophic Lateral Sclerosis Research (3 papers) and Tensor decomposition and applications (3 papers). Raghavendra Selvan is often cited by papers focused on Topic Modeling (3 papers), Amyotrophic Lateral Sclerosis Research (3 papers) and Tensor decomposition and applications (3 papers). Raghavendra Selvan collaborates with scholars based in Denmark, United Kingdom and United States. Raghavendra Selvan's co-authors include Ole Kiehn, Andy S. Anker, Kirsten M. Ø. Jensen, Peter Löw, Marleen de Bruijne, Harm A.W.M. Tiddens, Zaigham Saghir, Keith T. Butler, Simon J. L. Billinge and Mads R. V. Jørgensen and has published in prestigious journals such as Nature Communications, Nature Neuroscience and Scientific Reports.

In The Last Decade

Raghavendra Selvan

29 papers receiving 243 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raghavendra Selvan Denmark 8 59 45 33 30 27 32 246
Fatma Beyazal Çeliker Türkiye 10 21 0.4× 30 0.7× 23 0.7× 69 2.3× 10 0.4× 52 297
Junyu Chen China 11 104 1.8× 65 1.4× 14 0.4× 161 5.4× 29 1.1× 35 488
Yingying Bai China 13 15 0.3× 45 1.0× 24 0.7× 63 2.1× 34 1.3× 46 457
Yiming Lei China 8 8 0.1× 60 1.3× 16 0.5× 68 2.3× 13 0.5× 19 302
Tengyuan Zhou China 9 11 0.2× 57 1.3× 25 0.8× 10 0.3× 14 0.5× 15 258
Ruili Feng China 11 31 0.5× 28 0.6× 6 0.2× 17 0.6× 7 0.3× 34 375
H. Tang China 7 25 0.4× 8 0.2× 5 0.2× 55 1.8× 23 0.9× 15 335
Yukun Chen China 15 7 0.1× 53 1.2× 31 0.9× 83 2.8× 6 0.2× 33 426
Yiran Li China 10 35 0.6× 10 0.2× 16 0.5× 119 4.0× 3 0.1× 33 279
Prachi Singh United States 10 16 0.3× 32 0.7× 67 2.0× 142 4.7× 7 0.3× 22 374

Countries citing papers authored by Raghavendra Selvan

Since Specialization
Citations

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

Fields of papers citing papers by Raghavendra Selvan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raghavendra Selvan

This figure shows the co-authorship network connecting the top 25 collaborators of Raghavendra Selvan. A scholar is included among the top collaborators of Raghavendra Selvan 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 Raghavendra Selvan. Raghavendra Selvan 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.
Selvan, Raghavendra, et al.. (2025). PePR:Performance Per Resource Unit as a Metric to Promote Small-Scale Deep Learning in Medical Image Analysis. Research at the University of Copenhagen (University of Copenhagen).
2.
Selvan, Raghavendra, et al.. (2024). High‐throughput classification of S. cerevisiae tetrads using deep learning. Yeast. 41(7). 423–436.
3.
Sørensen, Andreas T., et al.. (2024). Stabilization of V1 interneuron-motor neuron connectivity ameliorates motor phenotype in a mouse model of ALS. Nature Communications. 15(1). 4867–4867. 6 indexed citations
4.
Selvan, Raghavendra, et al.. (2024). Spinal inhibitory neurons degenerate before motor neurons and excitatory neurons in a mouse model of ALS. Science Advances. 10(22). eadk3229–eadk3229. 7 indexed citations
5.
Anker, Andy S., et al.. (2024). A GPU-Accelerated Open-Source Python Package forCalculating Powder Diffraction, Small-Angle-, and Total Scattering withthe Debye Scattering Equation. The Journal of Open Source Software. 9(94). 6024–6024. 6 indexed citations
6.
Bhagwat, Nikhil, R. D. Wilkinson, Niall W. Duncan, et al.. (2024). Measuring and reducing the carbon footprint of fMRI preprocessing in fMRIPrep. Human Brain Mapping. 45(12). e70003–e70003. 4 indexed citations
7.
Selvan, Raghavendra, et al.. (2024). Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization. Research at the University of Copenhagen (University of Copenhagen). 24. 7430–7434. 1 indexed citations
8.
Igel, Christian, et al.. (2024). EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search. Research at the University of Copenhagen (University of Copenhagen). 5660–5664. 5 indexed citations
9.
Anker, Andy S., Keith T. Butler, Raghavendra Selvan, & Kirsten M. Ø. Jensen. (2023). Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry. Chemical Science. 14(48). 14003–14019. 23 indexed citations
10.
Selvan, Raghavendra, et al.. (2023). Pedunculopontine Chx10+ neurons control global motor arrest in mice. Nature Neuroscience. 26(9). 1516–1528. 15 indexed citations
11.
Martinsen, Kenneth Thorø, Kaj Sand‐Jensen, & Raghavendra Selvan. (2023). Predicting lake bathymetry from the topography of the surrounding terrain using deep learning. Limnology and Oceanography Methods. 21(10). 625–636. 5 indexed citations
12.
Selvan, Raghavendra, et al.. (2023). Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation. Research at the University of Copenhagen (University of Copenhagen). 4. 6 indexed citations
13.
Lannelongue, Loïc, Gabrielle Samuel, Lincoln Colling, et al.. (2023). Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging. Imaging Neuroscience. 1. 10 indexed citations
14.
Selvan, Raghavendra, et al.. (2022). Patch-based Medical Image Segmentation using Matrix Product State Tensor Networks. 1(IPMI 2021). 1–24. 1 indexed citations
15.
Anker, Andy S., Mikkel Juelsholt, Troels Lindahl Christiansen, et al.. (2022). Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning. npj Computational Materials. 8(1). 29 indexed citations
16.
Anker, Andy S., et al.. (2022). DeepStruc: towards structure solution from pair distribution function data using deep generative models. Digital Discovery. 2(1). 69–80. 17 indexed citations
17.
Selvan, Raghavendra, et al.. (2021). Locomotor deficits in a mouse model of ALS are paralleled by loss of V1-interneuron connections onto fast motor neurons. Nature Communications. 12(1). 3251–3251. 47 indexed citations
18.
Selvan, Raghavendra, et al.. (2021). Locally orderless tensor networks for classifying two- and three-dimensional medical images. 1(MIDL 2020). 1–21. 3 indexed citations
19.
Selvan, Raghavendra, et al.. (2021). An Efficient Social Spider Optimization Algorithm Based Multi-Document Summarization Model. 855–860. 1 indexed citations
20.
Petersen, Jens, Raghavendra Selvan, Daniël Bos, et al.. (2019). Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies. IEEE Transactions on Medical Imaging. 38(7). 1559–1568. 4 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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