Deepak M. Kirpalani

613 citations
26 papers · 460 indexed · h-index 13

Deepak M. Kirpalani

26 papers receiving 448 citations

Peers

Deepak M. Kirpalani
Comparison fields: 5 of 68
  • Water Science and Technology 94
  • Filtration and Separation 11
  • Analytical Chemistry 49
  • Biomedical Engineering 183
  • Computational Mechanics 84
Replace Sreepriya Vedantam with:
Sreepriya Vedantam India
Cláudio P. Fonte United Kingdom
Alex R. Heath Australia
Kreangkrai Maneeintr Thailand
Paul Bussmann Netherlands
Abulhassan Ali Saudi Arabia
Andreas Fredriksson Sweden
Bekir Zühtü Uysal Türkiye
Qiang Xie China
Takuo Sugawara Japan
Deepak M. Kirpalani relative to Sreepriya Vedantam India Sreepriya Vedantam's profile →
Citations per field
00.5×3.8×
Sreepriya Vedantam · 1×
Citations per year

Countries citing papers authored by Deepak M. Kirpalani

Since Specialization
Citations

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

Fields of papers citing papers by Deepak M. Kirpalani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deepak M. Kirpalani. 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 Deepak M. Kirpalani. The network helps show where Deepak M. Kirpalani may publish in the future.

Co-authorship network

The 13 scholars most cited alongside Deepak M. Kirpalani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Deepak M. Kirpalani Line = papers co-authored together Deepak M. Kirpalani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20224
2 20227
3 20223
4 201912
5 201954
6 20176
7 201624
8 201112
9 20116
10 201027
11 200910
12 200914
13 200810
14 20078
15 200712
16 200617
17 200556
18 20045
19 200247
20 200220

About Deepak M. Kirpalani

Deepak M. Kirpalani is a scholar working on Analytical Chemistry, Computational Mechanics, Biomedical Engineering, Water Science and Technology and Ocean Engineering, having authored 26 papers that have together received 460 indexed citations. Recurring topics across this work include Fluid Dynamics and Mixing (9 papers), Electrohydrodynamics and Fluid Dynamics (6 papers), Petroleum Processing and Analysis (5 papers), Ultrasound and Cavitation Phenomena (5 papers), Membrane Separation Technologies (4 papers), Fluid Dynamics and Heat Transfer (4 papers), Enhanced Oil Recovery Techniques (4 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (3 papers). The work is most often cited by research in Water Science and Technology (94 citations), Filtration and Separation (11 citations), Analytical Chemistry (49 citations), Biomedical Engineering (183 citations) and Computational Mechanics (84 citations). Deepak M. Kirpalani has collaborated with scholars based in Canada, United States and Japan. Frequent co-authors include Kenji Suzuki, Arturo Macchi, Adam Donaldson, Ashwani Kumar, Poupak Mehrani, Ayako Matsuoka, Susumu Nii, Michèle C. Loewen, Ajeet Kumar and Andy Nong. Their work appears in journals such as Ultrasonics Sonochemistry, Chemical Engineering and Processing - Process Intensification, International Journal of Multiphase Flow, Chemical Engineering & Technology and The Canadian Journal of Chemical Engineering.

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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