Kamalaker Dadi

1.7k total citations
8 papers, 270 citations indexed

About

Kamalaker Dadi is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Molecular Biology. According to data from OpenAlex, Kamalaker Dadi has authored 8 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cognitive Neuroscience, 2 papers in Experimental and Cognitive Psychology and 1 paper in Molecular Biology. Recurrent topics in Kamalaker Dadi's work include Functional Brain Connectivity Studies (7 papers), Neural dynamics and brain function (3 papers) and EEG and Brain-Computer Interfaces (2 papers). Kamalaker Dadi is often cited by papers focused on Functional Brain Connectivity Studies (7 papers), Neural dynamics and brain function (3 papers) and EEG and Brain-Computer Interfaces (2 papers). Kamalaker Dadi collaborates with scholars based in France, India and United States. Kamalaker Dadi's co-authors include Gaël Varoquaux, Bertrand Thirion, Alexandre Abraham, Milham Michael, Darya Chyzhyk, Mehdi Rahim, Denis A. Engemann, Josselin Houenou, Danilo Bzdok and Raju S. Bapi and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Neurobiology of Aging.

In The Last Decade

Kamalaker Dadi

7 papers receiving 270 citations

Peers

Kamalaker Dadi

CN

RNMI

ECP

PMH

AI

Johanna Bayer Australia

Ying Xing China

Nils R. Winter Germany

Deepthi P. Varikuti Germany

Ramona Leenings Germany

Pierre Berthet Norway

Gemeng Zhang United States

Weizheng Yan United States

Harini Eavani United States

Johanna Bayer Australia

Kamalaker Dadi

159 ×0.7

CN

98 ×1.2

RNMI

48 ×0.8

ECP

34 ×1.1

PMH

25 ×1.0

AI

Citations per year, relative to Kamalaker Dadi Kamalaker Dadi (= 1×) peers Johanna Bayer

Countries citing papers authored by Kamalaker Dadi

Since Specialization

Citations

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

Fields of papers citing papers by Kamalaker Dadi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kamalaker Dadi

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

All Works

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8 of 8 papers shown

1.

Jain, Chirag, et al.. (2024). HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable HyperEdges. 1–8.

2.

Dadi, Kamalaker, et al.. (2023). Dynamic functional connectivity analysis in individuals with Autism Spectrum Disorder. 15. 1–7. 1 indexed citations

3.

Liem, Franziskus, Kamalaker Dadi, Denis A. Engemann, et al.. (2022). Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging. Neurobiology of Aging. 118. 55–65. 14 indexed citations

4.

Dadi, Kamalaker, et al.. (2022). Deep Learning Approach for Classification and Interpretation of Autism Spectrum Disorder. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 9 indexed citations

5.

Dadi, Kamalaker, Gaël Varoquaux, Josselin Houenou, et al.. (2021). Population modeling with machine learning can enhance measures of mental health. GigaScience. 10(10). 25 indexed citations

6.

Dadi, Kamalaker, Gaël Varoquaux, Krzysztof J. Gorgolewski, et al.. (2020). Fine-grain atlases of functional modes for fMRI analysis. NeuroImage. 221. 117126–117126. 1 indexed citations

7.

Dadi, Kamalaker, Mehdi Rahim, Alexandre Abraham, et al.. (2019). Benchmarking functional connectome-based predictive models for resting-state fMRI. NeuroImage. 192. 115–134. 212 indexed citations

8.

Huntenburg, Julia M., et al.. (2017). Loading and plotting of cortical surface representations in Nilearn. SHILAP Revista de lepidopterología. 3. 8 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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