Abhra Sarkar

571 total citations
27 papers, 337 citations indexed

About

Abhra Sarkar is a scholar working on Artificial Intelligence, Statistics and Probability and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Abhra Sarkar has authored 27 papers receiving a total of 337 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 12 papers in Statistics and Probability and 4 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Abhra Sarkar's work include Bayesian Methods and Mixture Models (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Statistical Methods and Inference (8 papers). Abhra Sarkar is often cited by papers focused on Bayesian Methods and Mixture Models (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Statistical Methods and Inference (8 papers). Abhra Sarkar collaborates with scholars based in United States, Australia and Switzerland. Abhra Sarkar's co-authors include Erich D. Jarvis, Jonathan Chabout, David B. Dunson, David B. Dunson, Bani K. Mallick, Raymond J. Carroll, Simon E. Fisher, Debdeep Pati, Giorgio Paulon and Bharath Chandrasekaran and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Technometrics.

In The Last Decade

Abhra Sarkar

25 papers receiving 335 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abhra Sarkar United States 9 136 132 61 60 48 27 337
Yayoi Teramoto United Kingdom 6 143 1.1× 72 0.5× 67 1.1× 38 0.6× 3 0.1× 7 285
Diana A. Liao United States 9 207 1.5× 99 0.8× 93 1.5× 37 0.6× 7 0.1× 12 312
Michelle Spierings Netherlands 12 213 1.6× 55 0.4× 137 2.2× 6 0.1× 10 0.2× 16 375
Douglas K. Bemis United States 8 127 0.9× 91 0.7× 86 1.4× 10 0.2× 20 0.4× 9 576
Josep B. Trobalón Spain 6 69 0.5× 27 0.2× 15 0.2× 25 0.4× 8 0.2× 8 366
Lena Veit Germany 9 205 1.5× 121 0.9× 207 3.4× 3 0.1× 44 0.9× 14 410
Akihiro Izumi Japan 12 223 1.6× 201 1.5× 103 1.7× 11 0.2× 4 0.1× 31 590
Morgan L. Gustison United States 12 233 1.7× 210 1.6× 155 2.5× 17 0.3× 18 386
Kenta Suzuki Japan 13 378 2.8× 92 0.7× 288 4.7× 18 0.3× 2 0.0× 32 583
G. Marcus United States 4 46 0.3× 42 0.3× 13 0.2× 15 0.3× 50 1.0× 8 836

Countries citing papers authored by Abhra Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Abhra Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhra Sarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Abhra Sarkar. A scholar is included among the top collaborators of Abhra Sarkar 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 Abhra Sarkar. Abhra Sarkar 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.
Paulon, Giorgio, et al.. (2024). Individual differences in working memory impact the trajectory of non-native speech category learning. PLoS ONE. 19(6). e0297917–e0297917. 1 indexed citations
2.
3.
Müller, Peter, et al.. (2024). Bayesian Scalable Precision Factor Analysis for Gaussian Graphical Models. Bayesian Analysis. 21(1). 1 indexed citations
4.
Sarkar, Abhra, et al.. (2024). Bayesian semiparametric inference in longitudinal metabolomics data. Scientific Reports. 14(1). 31336–31336.
5.
Quinto‐Pozos, David, et al.. (2023). L2 Learners’ Signed Language Processing Relates, in Part, to Perspective‐Taking Skills. Language Learning. 73(S1). 64–100. 2 indexed citations
6.
Sarkar, Abhra, et al.. (2023). Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials. Journal of the American Statistical Association. 118(544). 2301–2314. 4 indexed citations
7.
Paulon, Giorgio, Peter Müller, & Abhra Sarkar. (2023). Bayesian Semiparametric Hidden Markov Tensor Models for Time Varying Random Partitions with Local Variable Selection. Bayesian Analysis. 19(4). 1 indexed citations
8.
Sarkar, Abhra, et al.. (2023). Bayesian Semiparametric Local Clustering of Multiple Time Series Data. Technometrics. 66(2). 282–294.
9.
Müller, P., et al.. (2023). Bayesian approaches to include real-world data in clinical studies. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 381(2247). 20220158–20220158. 5 indexed citations
10.
Sarkar, Abhra. (2022). Bayesian Semiparametric Covariate Informed Multivariate Density Deconvolution. Journal of Computational and Graphical Statistics. 31(4). 1153–1163. 1 indexed citations
11.
Paulon, Giorgio, et al.. (2021). Comparing perceptual category learning across modalities in the same individuals. Psychonomic Bulletin & Review. 28(3). 898–909. 9 indexed citations
12.
Sarkar, Abhra, Debdeep Pati, Bani K. Mallick, & Raymond J. Carroll. (2020). Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology. Journal of the American Statistical Association. 116(535). 1075–1087. 4 indexed citations
13.
Paulon, Giorgio, Fernando Llanos, Bharath Chandrasekaran, & Abhra Sarkar. (2020). Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults. Journal of the American Statistical Association. 116(535). 1114–1127. 7 indexed citations
14.
Paulon, Giorgio, Rachel Reetzke, Bharath Chandrasekaran, & Abhra Sarkar. (2019). Functional Logistic Mixed-Effects Models for Learning Curves From Longitudinal Binary Data. Journal of Speech Language and Hearing Research. 62(3). 543–553. 2 indexed citations
15.
Sarkar, Abhra, et al.. (2018). Bayesian Semiparametric Mixed Effects Markov Models With Application to Vocalization Syntax. Journal of the American Statistical Association. 113(524). 1515–1527. 5 indexed citations
16.
Chakraborty, Mukta, Liangfu Chen, Emma E. Fridel, et al.. (2017). Overexpression of human NR2B receptor subunit in LMAN causes stuttering and song sequence changes in adult zebra finches. Scientific Reports. 7(1). 942–942. 13 indexed citations
17.
Chabout, Jonathan, et al.. (2016). A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice. Frontiers in Behavioral Neuroscience. 10. 197–197. 69 indexed citations
18.
Sarkar, Abhra & David B. Dunson. (2016). Bayesian Nonparametric Modeling of Higher Order Markov Chains. Journal of the American Statistical Association. 111(516). 1791–1803. 13 indexed citations
19.
Chabout, Jonathan, Abhra Sarkar, David B. Dunson, & Erich D. Jarvis. (2015). Male mice song syntax depends on social contexts and influences female preferences. Frontiers in Behavioral Neuroscience. 9. 76–76. 145 indexed citations
20.
Sarkar, Abhra, Bani K. Mallick, John Staudenmayer, Debdeep Pati, & Raymond J. Carroll. (2014). Bayesian Semiparametric Density Deconvolution in the Presence of Conditionally Heteroscedastic Measurement Errors. Journal of Computational and Graphical Statistics. 23(4). 1101–1125. 13 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Yayoi Teramoto Breakdown of academic impact, for papers by Diana A. Liao Breakdown of academic impact, for papers by Michelle Spierings Breakdown of academic impact, for papers by Douglas K. Bemis Breakdown of academic impact, for papers by Josep B. Trobalón Breakdown of academic impact, for papers by Lena Veit Breakdown of academic impact, for papers by Akihiro Izumi Breakdown of academic impact, for papers by Morgan L. Gustison Breakdown of academic impact, for papers by Kenta Suzuki Breakdown of academic impact, for papers by G. Marcus
Rankless by CCL
2026