Sourabh Bhattacharya

491 total citations
26 papers, 248 citations indexed

About

Sourabh Bhattacharya is a scholar working on Artificial Intelligence, Statistics and Probability and Environmental Engineering. According to data from OpenAlex, Sourabh Bhattacharya has authored 26 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 11 papers in Statistics and Probability and 6 papers in Environmental Engineering. Recurrent topics in Sourabh Bhattacharya's work include Bayesian Methods and Mixture Models (11 papers), Statistical Methods and Bayesian Inference (6 papers) and Soil Geostatistics and Mapping (6 papers). Sourabh Bhattacharya is often cited by papers focused on Bayesian Methods and Mixture Models (11 papers), Statistical Methods and Bayesian Inference (6 papers) and Soil Geostatistics and Mapping (6 papers). Sourabh Bhattacharya collaborates with scholars based in India, United States and United Kingdom. Sourabh Bhattacharya's co-authors include John Haslett, Fraser Mitchell, Brian Huntley, Judy R M Allen, Michael Salter‐Townshend, Simon Wilson, Ashis SenGupta, Arunabha Majumdar, John S. Witte and Moon‐Ho Ringo Ho and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Biometrics.

In The Last Decade

Sourabh Bhattacharya

22 papers receiving 236 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sourabh Bhattacharya India 7 88 84 51 39 28 26 248
Leena Pasanen Finland 12 18 0.2× 115 1.4× 128 2.5× 16 0.4× 36 1.3× 23 270
Mark Irwin United States 9 34 0.4× 14 0.2× 36 0.7× 23 0.6× 21 0.8× 23 272
Ute Hahn Denmark 12 22 0.3× 26 0.3× 10 0.2× 18 0.5× 32 1.1× 32 342
Alfonso García‐Pérez Spain 9 28 0.3× 22 0.3× 20 0.4× 48 1.2× 6 0.2× 27 377
Christian Schäfer Germany 9 39 0.4× 53 0.6× 82 1.6× 33 0.8× 7 0.3× 15 374
Kari Vasko Finland 6 61 0.7× 168 2.0× 23 0.5× 4 0.1× 10 0.4× 6 355
Anne Cuzol France 8 42 0.5× 71 0.8× 84 1.6× 7 0.2× 34 1.2× 15 271
Hao Long China 9 32 0.4× 82 1.0× 90 1.8× 15 0.4× 9 0.3× 39 427
Marco Oesting Germany 9 40 0.5× 20 0.2× 127 2.5× 76 1.9× 80 2.9× 22 327
Nicholas R. Cavanaugh United States 8 28 0.3× 223 2.7× 261 5.1× 11 0.3× 20 0.7× 10 374

Countries citing papers authored by Sourabh Bhattacharya

Since Specialization
Citations

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

Fields of papers citing papers by Sourabh Bhattacharya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sourabh Bhattacharya

This figure shows the co-authorship network connecting the top 25 collaborators of Sourabh Bhattacharya. A scholar is included among the top collaborators of Sourabh Bhattacharya 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 Sourabh Bhattacharya. Sourabh Bhattacharya 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.
2.
Bhattacharya, Sourabh, et al.. (2024). Disulfiram-induced psychosis still an important clinical entity: A case series. SHILAP Revista de lepidopterología. 33(Suppl 1). S229–S232.
3.
4.
Majumdar, Arunabha, Tanushree Haldar, Sourabh Bhattacharya, & John S. Witte. (2018). An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations. PLoS Genetics. 14(2). e1007139–e1007139. 28 indexed citations
5.
Bhattacharya, Sourabh, et al.. (2016). A note on the misuses of the variance test in meteorological studies. Meteorology and Atmospheric Physics. 129(6). 645–658. 2 indexed citations
6.
Biswas, Munmun, et al.. (2015). Bayesian nonparametric estimation of Milky Way parameters using matrix-variate data, in a new Gaussian Process based method. Electronic Journal of Statistics. 9(1). 2 indexed citations
7.
SenGupta, Ashis & Sourabh Bhattacharya. (2015). Finite mixture-based Bayesian analysis of linear-circular models. Environmental and Ecological Statistics. 22(4). 667–679. 1 indexed citations
8.
Bhattacharya, Sourabh, et al.. (2015). Bayesian nonparametric dynamic state space modeling with circular latent states. Journal of Statistical Theory and Practice. 10(1). 154–178.
9.
Majumdar, Arunabha, Sourabh Bhattacharya, Analabha Basu, & Saurabh Ghosh. (2013). A Novel Bayesian Semiparametric Algorithm for Inferring Population Structure and Adjusting for Case‐Control Association Tests. Biometrics. 69(1). 164–173. 3 indexed citations
10.
Berrocal, Veronica J., Marie Lynn Miranda, Alan E. Gelfand, & Sourabh Bhattacharya. (2013). Synthesizing categorical datasets to enhance inference. Statistical Methodology. 15. 25–45. 1 indexed citations
11.
Bhattacharya, Sourabh & Ranjan Maitra. (2011). A nonstationary nonparametric Bayesian approach to dynamically modeling effective connectivity in functional magnetic resonance imaging experiments. The Annals of Applied Statistics. 5(2B). 5 indexed citations
12.
Bhattacharya, Sourabh, et al.. (2011). On Bayesian “central clustering”: Application to landscape classification of Western Ghats. The Annals of Applied Statistics. 5(3). 4 indexed citations
13.
Bhattacharya, Sourabh & Ashis SenGupta. (2009). Bayesian analysis of semiparametric linear-circular models. Journal of Agricultural Biological and Environmental Statistics. 14(1). 33–65. 17 indexed citations
14.
Bhattacharya, Sourabh. (2008). Consistent estimation of the accuracy of importance sampling using regenerative simulation. Statistics & Probability Letters. 78(15). 2522–2527. 3 indexed citations
15.
Bhattacharya, Sourabh, Alan E. Gelfand, & Kent E. Holsinger. (2007). Model fitting and inference under latent equilibrium processes. Statistics and Computing. 17(2). 193–208. 3 indexed citations
16.
Bhattacharya, Sourabh & John Haslett. (2007). Importance re-sampling {MCMC} for cross-validation in inverse problems. Bayesian Analysis. 2(2). 6 indexed citations
17.
Bhattacharya, Sourabh. (2007). A methodology for sensitivity analysis in inverse problems—application to a palaeoclimate study. Environmetrics. 18(6). 647–660. 1 indexed citations
18.
Haslett, John, Sourabh Bhattacharya, Michael Salter‐Townshend, et al.. (2006). Bayesian Palaeoclimate Reconstruction. Journal of the Royal Statistical Society Series A (Statistics in Society). 169(3). 395–438. 101 indexed citations
19.
Bhattacharya, Sourabh. (2006). A Bayesian semiparametric model for organism based environmental reconstruction. Environmetrics. 17(7). 763–776. 6 indexed citations
20.
Bhattacharya, Sourabh, et al.. (2005). A Bayesian approach to modeling dynamic effective connectivity with fMRI data. NeuroImage. 30(3). 794–812. 20 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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