Jyotishka Datta

2.0k total citations
31 papers, 284 citations indexed

About

Jyotishka Datta is a scholar working on Statistics and Probability, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Jyotishka Datta has authored 31 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics and Probability, 7 papers in Artificial Intelligence and 4 papers in Sociology and Political Science. Recurrent topics in Jyotishka Datta's work include Statistical Methods and Inference (11 papers), Statistical Methods and Bayesian Inference (7 papers) and Bayesian Methods and Mixture Models (5 papers). Jyotishka Datta is often cited by papers focused on Statistical Methods and Inference (11 papers), Statistical Methods and Bayesian Inference (7 papers) and Bayesian Methods and Mixture Models (5 papers). Jyotishka Datta collaborates with scholars based in United States, India and Singapore. Jyotishka Datta's co-authors include Jayanta K. Ghosh, Edward L. Bartlett, Aravindakshan Parthasarathy, Anindya Bhadra, Philip Schoeneberger, David B. Dunson, Zamir Libohova, Phillip Owens, H. Winzeler and Yunfan Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Blood.

In The Last Decade

Jyotishka Datta

28 papers receiving 276 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jyotishka Datta United States 9 63 45 38 36 35 31 284
Dario Basso Italy 11 73 1.2× 18 0.4× 86 2.3× 35 1.0× 2 0.1× 14 364
Cristina Rueda Spain 12 94 1.5× 50 1.1× 51 1.3× 49 1.4× 1 0.0× 52 405
Lamiae Azizi Australia 11 35 0.6× 58 1.3× 37 1.0× 58 1.6× 1 0.0× 20 454
C. Weber United States 6 31 0.5× 11 0.2× 24 0.6× 56 1.6× 2 0.1× 15 272
Fentaw Abegaz Netherlands 11 62 1.0× 26 0.6× 69 1.8× 43 1.2× 1 0.0× 33 347
Frank Dondelinger United Kingdom 11 30 0.5× 18 0.4× 209 5.5× 119 3.3× 2 0.1× 32 490
Jiangtao Gou United States 12 158 2.5× 38 0.8× 71 1.9× 16 0.4× 45 351
Hervé Perdry France 13 36 0.6× 24 0.5× 85 2.2× 12 0.3× 2 0.1× 48 441
FRANK A. BARNES United States 3 14 0.2× 26 0.6× 31 0.8× 19 0.5× 9 0.3× 5 620
Mateja Blas Slovenia 8 17 0.3× 12 0.3× 28 0.7× 34 0.9× 9 434

Countries citing papers authored by Jyotishka Datta

Since Specialization
Citations

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

Fields of papers citing papers by Jyotishka Datta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jyotishka Datta

This figure shows the co-authorship network connecting the top 25 collaborators of Jyotishka Datta. A scholar is included among the top collaborators of Jyotishka Datta 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 Jyotishka Datta. Jyotishka Datta 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.
Datta, Jyotishka, et al.. (2024). Maximum a posteriori estimation in graphical models using local linear approximation. Stat. 13(2). 2 indexed citations
2.
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Bhadra, Anindya, et al.. (2024). Merging two cultures: Deep and statistical learning. Wiley Interdisciplinary Reviews Computational Statistics. 16(2). 1 indexed citations
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5.
Datta, Jyotishka, Debashree Ray, Swapnil Mishra, et al.. (2023). Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021. SHILAP Revista de lepidopterología. 3(12). e0002063–e0002063.
6.
Boss, Jonathan, Jyotishka Datta, Xin Wang, et al.. (2023). Group Inverse-Gamma Gamma Shrinkage for Sparse Linear Models with Block-Correlated Regressors. Bayesian Analysis. 19(3). 2 indexed citations
7.
Drawve, Grant, et al.. (2023). Quantifying the Effect of Socio-Economic Predictors and the Built Environment on Mental Health Events in Little Rock, AR. ISPRS International Journal of Geo-Information. 12(5). 205–205. 1 indexed citations
8.
Harris, Casey T., et al.. (2022). Innovative data in communities and crime research: an example at the intersection of racial segregation, neighborhood permeability, and crime. Journal of Crime and Justice. 45(5). 609–626. 1 indexed citations
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10.
Brown, Clare C., et al.. (2021). Understanding racial disparities in severe maternal morbidity using Bayesian network analysis. PLoS ONE. 16(10). e0259258–e0259258. 3 indexed citations
11.
Datta, Jyotishka, et al.. (2021). A Meta-Analysis of the Protein Components in Rattlesnake Venom. Toxins. 13(6). 372–372. 13 indexed citations
12.
Chaudhuri, Jasodhara, Tamoghna Biswas, Jyotishka Datta, et al.. (2021). Correlation of ATP7B gene mutations with clinical phenotype and radiological features in Indian Wilson disease patients. Acta Neurologica Belgica. 122(1). 181–190. 2 indexed citations
13.
Datta, Jyotishka & Bhramar Mukherjee. (2021). Discussion on “Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data”. Journal of the American Statistical Association. 116(536). 1583–1586. 2 indexed citations
14.
Datta, Jyotishka, et al.. (2020). Improving Spatial Visualization Abilities Using 3D Printed Blocks. 3 indexed citations
15.
Bhadra, Anindya, Jyotishka Datta, Yunfan Li, & Nicholas Polson. (2020). Horseshoe Regularisation for Machine Learning in Complex and Deep Models1. International Statistical Review. 88(2). 302–320. 12 indexed citations
16.
Drawve, Grant, et al.. (2020). Risky Business: Examining the 80-20 Rule in Relation to a RTM Framework. Criminal Justice Review. 46(1). 20–39. 4 indexed citations
17.
Bhadra, Anindya, et al.. (2017). Lasso Meets Horseshoe. arXiv (Cornell University). 2 indexed citations
18.
Chaudhuri, Jasodhara, et al.. (2016). Evaluation of malnutrition as a predictor of adverse outcomes in febrile neutropenia associated with paediatric haematological malignancies. Journal of Paediatrics and Child Health. 52(7). 704–709. 6 indexed citations
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Parthasarathy, Aravindakshan, et al.. (2014). Age-Related Changes in the Relationship Between Auditory Brainstem Responses and Envelope-Following Responses. Journal of the Association for Research in Otolaryngology. 15(4). 649–661. 48 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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