Debashis Paul

3.2k total citations · 1 hit paper
42 papers, 1.7k citations indexed

About

Debashis Paul is a scholar working on Statistics and Probability, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Debashis Paul has authored 42 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 9 papers in Environmental Engineering. Recurrent topics in Debashis Paul's work include Random Matrices and Applications (11 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Inference (9 papers). Debashis Paul is often cited by papers focused on Random Matrices and Applications (11 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Inference (9 papers). Debashis Paul collaborates with scholars based in United States, China and Australia. Debashis Paul's co-authors include Eric Bair, Trevor Hastie, Robert Tibshirani, Jie Peng, Iain M. Johnstone, Alexander Aue, R. Narasimhan, Ping Li, J.M. Cioffi and Jack W. Silverstein and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Proceedings of the IEEE.

In The Last Decade

Debashis Paul

38 papers receiving 1.7k citations

Hit Papers

Prediction by Supervised Principal Components 2006 2026 2012 2019 2006 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Prediction by Supervised Principal Components
    2006 523 citations Debashis Paul et al. Journal of the American Statistical Association profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debashis Paul United States 15 734 377 280 220 179 42 1.7k
John P. Nolan United States 22 348 0.5× 213 0.6× 130 0.5× 170 0.8× 74 0.4× 61 1.8k
James R. Schott United States 19 745 1.0× 346 0.9× 88 0.3× 103 0.5× 84 0.5× 46 1.6k
Ery Arias-Castro United States 19 317 0.4× 541 1.4× 143 0.5× 154 0.7× 117 0.7× 60 1.5k
Andrew L. Rukhin United States 21 889 1.2× 617 1.6× 102 0.4× 115 0.5× 126 0.7× 160 2.6k
Alessandro Rinaldo United States 20 567 0.8× 565 1.5× 139 0.5× 39 0.2× 60 0.3× 57 1.5k
Vladimir Spokoiny Germany 25 1.3k 1.7× 679 1.8× 90 0.3× 66 0.3× 128 0.7× 107 2.7k
Colin L. Mallows United States 15 519 0.7× 271 0.7× 50 0.2× 295 1.3× 172 1.0× 55 1.7k
Guillaume Obozinski Switzerland 15 362 0.5× 700 1.9× 258 0.9× 77 0.3× 79 0.4× 38 2.0k
Morris L. Eaton United States 22 1.2k 1.6× 536 1.4× 78 0.3× 115 0.5× 86 0.5× 71 2.3k

Countries citing papers authored by Debashis Paul

Since Specialization
Citations

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

Fields of papers citing papers by Debashis Paul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debashis Paul

This figure shows the co-authorship network connecting the top 25 collaborators of Debashis Paul. A scholar is included among the top collaborators of Debashis Paul 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 Debashis Paul. Debashis Paul 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.
Lee, Thomas C. M., et al.. (2024). Estimating fiber orientation distribution with application to study brain lateralization using HCP D-MRI data. The Annals of Applied Statistics. 18(1). 100–124.
2.
Chakraborty, Joyeeta, Aditi Chandra, Debashis Paul, et al.. (2024). Universal penalized regression (Elastic-net) model with differentially methylated promoters for oral cancer prediction. European journal of medical research. 29(1). 458–458. 3 indexed citations
3.
Paul, Debashis, et al.. (2022). Inference on the dynamics of COVID-19 in the United States. Scientific Reports. 12(1). 2253–2253. 5 indexed citations
4.
Matsuo, Tomoko, Minjie Fan, Xueling Shi, et al.. (2021). Multiresolution Modeling of High‐Latitude Ionospheric Electric Field Variability and Impact on Joule Heating Using SuperDARN Data. Journal of Geophysical Research Space Physics. 126(9). e2021JA029196–e2021JA029196. 5 indexed citations
5.
Paul, Debashis, et al.. (2021). Introducing uncertainty quantification to techno-economic models of manufacturing field-grown plant-made products. Food and Bioproducts Processing. 128. 153–165. 6 indexed citations
6.
Paul, Debashis, et al.. (2021). Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing. SHILAP Revista de lepidopterología. 38. 107317–107317. 4 indexed citations
7.
Aue, Alexander, et al.. (2020). An adaptable generalization of Hotelling’s $T^{2}$ test in high dimension. The Annals of Statistics. 48(3). 17 indexed citations
8.
Johnstone, Iain M. & Debashis Paul. (2018). PCA in High Dimensions: An Orientation. Proceedings of the IEEE. 106(8). 1277–1292. 71 indexed citations
9.
10.
Yan, Hao, Owen Carmichael, Debashis Paul, & Jie Peng. (2018). Estimating fiber orientation distribution from diffusion MRI with spherical needlets. Medical Image Analysis. 46. 57–72. 5 indexed citations
11.
Fan, Minjie, Debashis Paul, Thomas C. M. Lee, & Tomoko Matsuo. (2018). A multi-resolution model for non-Gaussian random fields on a sphere with application to ionospheric electrostatic potentials. The Annals of Applied Statistics. 12(1). 459–489. 6 indexed citations
12.
Danaher, Patrick, Debashis Paul, & Pei Wang. (2015). Covariance-based analyses of biological pathways. Biometrika. 102(3). 533–544. 2 indexed citations
13.
Wang, Lili & Debashis Paul. (2014). Limiting spectral distribution of renormalized separable sample covariance matrices whenp/n→0. Journal of Multivariate Analysis. 126. 25–52. 12 indexed citations
14.
Johnstone, Iain M., et al.. (2013). Minimax bounds for sparse PCA with noisy high-dimensional data. The Annals of Statistics. 41(3). 1055–1084. 77 indexed citations
15.
Carmichael, Owen, Jun Chen, Debashis Paul, & Jie Peng. (2013). Diffusion tensor smoothing through weighted Karcher means. Electronic Journal of Statistics. 7(none). 1913–1956. 10 indexed citations
16.
Viswanath, Vish, Evan Fletcher, Baljeet Singh, et al.. (2012). Impact of DTI smoothing on the study of brain aging. PubMed. 11. 94–97. 2 indexed citations
17.
Chen, Lin, Debashis Paul, Ross L. Prentice, & Pei Wang. (2011). A Regularized Hotelling’sT2Test for Pathway Analysis in Proteomic Studies. Journal of the American Statistical Association. 106(496). 1345–1360. 61 indexed citations
18.
Kaye, Jason P., Anandamayee Majumdar, & Debashis Paul. (2010). Sensitivity analysis and model selection for a generalized convolution model for spatial processes. Bayesian Analysis. 5(3). 2 indexed citations
19.
Paul, Debashis & Jack W. Silverstein. (2008). No eigenvalues outside the support of the limiting empirical spectral distribution of a separable covariance matrix. Journal of Multivariate Analysis. 100(1). 37–57. 41 indexed citations
20.
Paul, Debashis. (2007). ASYMPTOTICS OF SAMPLE EIGENSTRUCTURE FOR A LARGE DIMENSIONAL SPIKED COVARIANCE MODEL. 330 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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