Prashant Rai

553 total citations
2 papers, 7 citations indexed

About

Prashant Rai is a scholar working on Computational Mathematics, Atomic and Molecular Physics, and Optics and Computational Mechanics. According to data from OpenAlex, Prashant Rai has authored 2 papers receiving a total of 7 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computational Mathematics, 2 papers in Atomic and Molecular Physics, and Optics and 1 paper in Computational Mechanics. Recurrent topics in Prashant Rai's work include Tensor decomposition and applications (2 papers), Advanced NMR Techniques and Applications (1 paper) and Sparse and Compressive Sensing Techniques (1 paper). Prashant Rai is often cited by papers focused on Tensor decomposition and applications (2 papers), Advanced NMR Techniques and Applications (1 paper) and Sparse and Compressive Sensing Techniques (1 paper). Prashant Rai collaborates with scholars based in United States. Prashant Rai's co-authors include Khachik Sargsyan, Habib N. Najm, So Hirata and Matthew R. Hermes and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering and Molecular Physics.

In The Last Decade

Prashant Rai

2 papers receiving 7 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Prashant Rai United States	2	4	3	2	2	2	2	7
M. Scott United States	3	3 0.8×		1 0.5×	1 0.5×		5	9
Huei Sears United Kingdom	2	2 0.5×					3	6
T. Fujino Japan	1			2 1.0×	1 0.5×		3	6
Y. Kida Japan	2			2 1.0×	1 0.5×		2	8
L. Beaufore Brazil	1				2 1.0×		2	2
Seonho Choi South Korea	2				2 1.0×		3	4
R. Walet Netherlands	2				2 1.0×	1 0.5×	3	5
Peter Doze Chile	2					2 1.0×	2	7
É. Lalande Canada	2				2 1.0×	1 0.5×	3	4
A. W. Lussier Canada	2				2 1.0×	1 0.5×	3	4

Countries citing papers authored by Prashant Rai

Since Specialization

Citations

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

Fields of papers citing papers by Prashant Rai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prashant Rai

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

All Works

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2 of 2 papers shown

1.

Rai, Prashant, Khachik Sargsyan, & Habib N. Najm. (2018). Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals. Computer Methods in Applied Mechanics and Engineering. 336. 471–484. 2 indexed citations

2.

Rai, Prashant, Khachik Sargsyan, Habib N. Najm, Matthew R. Hermes, & So Hirata. (2017). Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory. Molecular Physics. 115(17-18). 2120–2134. 5 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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