Charles A. Ellis

1.8k total citations
50 papers, 955 citations indexed

About

Charles A. Ellis is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine and Experimental and Cognitive Psychology. According to data from OpenAlex, Charles A. Ellis has authored 50 papers receiving a total of 955 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cognitive Neuroscience, 12 papers in Cardiology and Cardiovascular Medicine and 7 papers in Experimental and Cognitive Psychology. Recurrent topics in Charles A. Ellis's work include Functional Brain Connectivity Studies (24 papers), EEG and Brain-Computer Interfaces (21 papers) and ECG Monitoring and Analysis (12 papers). Charles A. Ellis is often cited by papers focused on Functional Brain Connectivity Studies (24 papers), EEG and Brain-Computer Interfaces (21 papers) and ECG Monitoring and Analysis (12 papers). Charles A. Ellis collaborates with scholars based in United States, Netherlands and Italy. Charles A. Ellis's co-authors include Louis Weinstein, Robyn L. Miller, Vince D. Calhoun, Jack L. LeFrock, David R. Snydman, Stephen J. Kornfeld, Heber MacMahon, Mohammad S.E. Sendi, Eric A. Engels and John B. Wong and has published in prestigious journals such as New England Journal of Medicine, SHILAP Revista de lepidopterología and Annals of Internal Medicine.

In The Last Decade

Charles A. Ellis

48 papers receiving 817 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Charles A. Ellis United States 14 228 224 208 133 122 50 955
Pinaki Biswas United States 25 583 2.6× 533 2.4× 67 0.3× 79 0.6× 75 0.6× 72 2.7k
R. Huttunen Finland 15 277 1.2× 371 1.7× 33 0.2× 199 1.5× 116 1.0× 25 1.1k
M. R. Visser Netherlands 22 175 0.8× 263 1.2× 20 0.1× 179 1.3× 78 0.6× 36 966
Lorenza Pugni Italy 20 323 1.4× 810 3.6× 36 0.2× 133 1.0× 337 2.8× 86 1.4k
Andrew Ferguson United Kingdom 11 183 0.8× 338 1.5× 64 0.3× 358 2.7× 184 1.5× 21 1.1k
Hung‐Chih Lin Taiwan 26 169 0.7× 285 1.3× 45 0.2× 306 2.3× 453 3.7× 82 1.9k
Nimrod Maimon Israel 17 166 0.7× 330 1.5× 53 0.3× 269 2.0× 475 3.9× 61 1.2k
Wai Ming Chan China 10 604 2.6× 359 1.6× 82 0.4× 148 1.1× 62 0.5× 29 1.2k
Paul Hshieh United States 16 150 0.7× 155 0.7× 15 0.1× 206 1.5× 97 0.8× 23 987
Ayper Somer Türkiye 18 263 1.2× 411 1.8× 12 0.1× 167 1.3× 181 1.5× 116 1.0k

Countries citing papers authored by Charles A. Ellis

Since Specialization
Citations

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

Fields of papers citing papers by Charles A. Ellis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles A. Ellis

This figure shows the co-authorship network connecting the top 25 collaborators of Charles A. Ellis. A scholar is included among the top collaborators of Charles A. Ellis 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 Charles A. Ellis. Charles A. Ellis 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.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2024). Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis. 1–5. 1 indexed citations
2.
Ellis, Charles A., et al.. (2024). Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer’s disease continuum. Network Neuroscience. 9(1). 259–279. 2 indexed citations
3.
Sendi, Mohammad S.E., Charles A. Ellis, Zening Fu, et al.. (2023). The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease. NeuroImage Clinical. 37. 103363–103363. 9 indexed citations
4.
5.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2023). A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis*. PubMed. 2023. 1–4. 2 indexed citations
6.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2023). Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations *. PubMed. 2023. 1–4. 1 indexed citations
7.
Ellis, Charles A., et al.. (2023). Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. Frontiers in Neuroinformatics. 17. 1123376–1123376. 9 indexed citations
8.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2023). Pairing explainable deep learning classification with clustering to uncover effects of schizophrenia upon whole brain functional network connectivity dynamics. SHILAP Revista de lepidopterología. 3(4). 100186–100186. 4 indexed citations
9.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2023). Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. 1–4. 3 indexed citations
10.
Ellis, Charles A., Robyn L. Miller, & Vince D. Calhoun. (2023). Towards greater neuroimaging classification transparency via the integration of explainability methods and confidence estimation approaches. Informatics in Medicine Unlocked. 37. 101176–101176. 7 indexed citations
11.
Ellis, Charles A., et al.. (2022). Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. 305–308. 10 indexed citations
12.
13.
Ellis, Charles A., et al.. (2021). A Novel Local Ablation Approach for Explaining Multimodal Classifiers. 1–6. 8 indexed citations
14.
Ellis, Charles A., Mohammad S.E. Sendi, Robyn L. Miller, & Vince D. Calhoun. (2021). A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 114. 3358–3365. 9 indexed citations
15.
Gawne, Timothy J., Meredith A. Reid, Nina V. Kraguljac, et al.. (2020). A multimodal magnetoencephalography 7 T fMRI and 7 T proton MR spectroscopy study in first episode psychosis. Schizophrenia. 6(1). 23–23. 18 indexed citations
16.
Ellis, Charles A., et al.. (1999). Life Expectancy Estimation with Breast Cancer: Bias of the Declining Exponential Function and an Alternative to Its Use. Medical Decision Making. 19(4). 385–393. 8 indexed citations
17.
Weinberg, Marc S., Charles A. Ellis, & S B Levy. (1980). Nutritionally deficient Streptococcus: investigation of the hidden culprit in culture-negative endocarditis.. PubMed. 73(12). 1647–9. 6 indexed citations
18.
Frock, Jack L. Le, et al.. (1975). Transient Bacteremia Associated with Percutaneous Liver Biopsy. The Journal of Infectious Diseases. 131(Supplement). S104–S107. 33 indexed citations
19.
LeFrock, Jack L., et al.. (1973). Transient Bacteremia Associated with Sigmoidoscopy. New England Journal of Medicine. 289(9). 467–469. 125 indexed citations
20.
Ellis, Charles A., et al.. (1967). The Significance of Candidemia. Annals of Internal Medicine. 67(3_Part_1). 511–522. 139 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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2026