Vishal Das

1.2k total citations · 1 hit paper
30 papers, 870 citations indexed

About

Vishal Das is a scholar working on Geophysics, Ocean Engineering and Mechanical Engineering. According to data from OpenAlex, Vishal Das has authored 30 papers receiving a total of 870 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Geophysics, 10 papers in Ocean Engineering and 10 papers in Mechanical Engineering. Recurrent topics in Vishal Das's work include Seismic Imaging and Inversion Techniques (16 papers), Hydraulic Fracturing and Reservoir Analysis (8 papers) and Drilling and Well Engineering (7 papers). Vishal Das is often cited by papers focused on Seismic Imaging and Inversion Techniques (16 papers), Hydraulic Fracturing and Reservoir Analysis (8 papers) and Drilling and Well Engineering (7 papers). Vishal Das collaborates with scholars based in United States, India and Israel. Vishal Das's co-authors include Tapan Mukerji, Uri Wollner, Ahinoam Pollack, Reetam Biswas, Mrinal K. Sen, Arvind Kumar Pandey, Gary Mavko, Sanyog Rawat, J. R. Kayal and Amit Singh and has published in prestigious journals such as The Journal of Physical Chemistry B, Geophysics and Computers & Geosciences.

In The Last Decade

Vishal Das

27 papers receiving 851 citations

Hit Papers

align trajectories

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.

Convolutional neural network for seismic impedance inversion

2019 304 citations Vishal Das, Ahinoam Pollack et al. Geophysics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vishal Das United States	12	636	465	338	124	102	30	870
Junxiao Li China	14	397 0.6×	293 0.6×	134 0.4×	52 0.4×	44 0.4×	64	706
Hirokazu Moriya Japan	16	455 0.7×	129 0.3×	176 0.5×	207 1.7×	35 0.3×	61	748
Shengjie Sun China	9	178 0.3×	100 0.2×	116 0.3×	155 1.3×	8 0.1×	23	370
Yongna Jia China	7	220 0.3×	105 0.2×	87 0.3×	12 0.1×	4 0.0×	10	331
C.M. Stone United States	11	131 0.2×	295 0.6×	361 1.1×	185 1.5×	14 0.1×	32	587
Reza Shams Iran	12	45 0.1×	246 0.5×	180 0.5×	127 1.0×	5 0.0×	19	453
Ziyuan Qi China	9	43 0.1×	424 0.9×	404 1.2×	428 3.5×	6 0.1×	26	648
Rujun Chen China	17	241 0.4×	157 0.3×	67 0.2×	31 0.3×	35 0.3×	73	1.3k
Shengwang Hao China	11	114 0.2×	62 0.1×	43 0.1×	211 1.7×	9 0.1×	39	445

Countries citing papers authored by Vishal Das

Since Specialization

Citations

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

Fields of papers citing papers by Vishal Das

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vishal Das

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

All Works

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20 of 20 papers shown

Rawat, Sanyog, et al.. (2024). Efficiency Enhanced Sneezewort Plant Inspired Antenna for mm-Wave Applications. 30(2). 71–81.

Das, Vishal, et al.. (2024). Formulation and Characterization of Silane Modified Acrylic Based Transparent Organic-Inorganic Hybrid Coatings for Improved Instrumented Indentation Hardness of PMMA. Silicon. 16(13-14). 5243–5256.

Saxena, Nishank, et al.. (2022). Estimation of Water Saturation in Shale Formation Using In Situ Multifrequency Dielectric Permittivity. Geofluids. 2022. 1–16. 3 indexed citations

Das, Vishal & Sanyog Rawat. (2021). Modified rectangular planar antenna with stubs and defected ground structure for THz applications. Optik. 242. 167292–167292. 11 indexed citations

Das, Vishal & Tapan Mukerji. (2020). Petrophysical properties prediction from prestack seismic data using convolutional neural networks. Geophysics. 85(5). N41–N55. 83 indexed citations

Das, Vishal, Tapan Mukerji, & Gary Mavko. (2019). Numerical simulation of coupled fluid-solid interaction at the pore scale: A digital rock-physics technology. Geophysics. 84(4). WA71–WA81. 18 indexed citations

Das, Vishal, Tapan Mukerji, & Gary Mavko. (2019). Scale effects of velocity dispersion and attenuation (Q⁻¹) in layered viscoelastic medium. Geophysics. 84(3). T147–T166. 6 indexed citations

Das, Vishal, Ahinoam Pollack, Uri Wollner, & Tapan Mukerji. (2019). Convolutional neural network for seismic impedance inversion. Geophysics. 84(6). R869–R880. 304 indexed citations breakdown →

Das, Vishal & Tapan Mukerji. (2019). Petrophysical properties prediction from pre-stack seismic data using convolutional neural networks. 2328–2332. 11 indexed citations

10.

Biswas, Reetam, Mrinal K. Sen, Vishal Das, & Tapan Mukerji. (2019). Prestack and poststack inversion using a physics-guided convolutional neural network. Interpretation. 7(3). SE161–SE174. 166 indexed citations

11.

Das, Vishal & Tapan Mukerji. (2019). Traditional Feature Based vs Direct Machine Learning Based AVO Classification. 81st EAGE Conference and Exhibition 2019. 1–5. 5 indexed citations

12.

Das, Vishal, Ahinoam Pollack, Uri Wollner, & Tapan Mukerji. (2018). Convolutional neural network for seismic impedance inversion. 2071–2075. 63 indexed citations

13.

Das, Vishal, Tapan Mukerji, & G. Mavko. (2017). Scale effects on velocity dispersion and attenuation (Q-1) in layered viscoelastic medium. 64. 3557–3562. 1 indexed citations

14.

Ramani, R., et al.. (2014). Free Volume Study on the Origin of Dielectric Constant in a Fluorine-Containing Polyimide Blend: Poly(vinylidene fluoride-co-hexafluoro propylene)/Poly(ether imide). The Journal of Physical Chemistry B. 118(42). 12282–12296. 41 indexed citations

15.

Das, Vishal, et al.. (2014). Studies on boost topologies for high boost ratio. 128. 762–766. 3 indexed citations

16.

Kayal, J. R., et al.. (2012). An Appraisal of the 2001 Bhuj Earthquake (Mw 7.7, India) Source Zone: Fractal Dimension and b Value Mapping of the Aftershock Sequence. Pure and Applied Geophysics. 169(12). 2127–2138. 23 indexed citations

17.

Das, Vishal, et al.. (2012). Compatibilization Efficacy of LLDPE-g-MA on Mechanical, Thermal, Morphological and Water Absorption Properties of Nylon-6/LLDPE Blends. Polymer-Plastics Technology and Engineering. 51(5). 446–454. 29 indexed citations

18.

Das, Vishal, et al.. (2011). Effect of SBS Content on Low Temperature Impact Strength, Morphology and Rheology of PP-cp/SBS Blends. Polymer-Plastics Technology and Engineering. 50(8). 825–832. 31 indexed citations

19.

Das, Vishal, Arvind Pandey, P. K. Giri, et al.. (2010). Effect of Shear Rate and Nanoclay Content on the Die Swell of Polypropylene Nanocomposites Extruded Under Capillary Flow. AIP conference proceedings. 288–293. 1 indexed citations

20.

Das, Vishal, et al.. (2008). Low Temperature Izod Impact Studies of Blends Based on Impact Grade Polypropylene and Ethylene-α-Octene Copolymer. Journal of Reinforced Plastics and Composites. 28(23). 2879–2888. 19 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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