Raghavendra V. Kulkarni

5.8k citations
101 papers · 4.2k indexed · 3 hit papers · h-index 30

Raghavendra V. Kulkarni

99 papers receiving 4.0k citations

Hit Papers

Convolutional neural netw...5282010202620152020100200300400500

Peers

Raghavendra V. Kulkarni
Comparison fields: 5 of 176
  • Molecular Medicine 681
  • Pharmaceutical Science 696
  • Computer Networks and Communications 1.1k
  • Biomaterials 467
  • Ocean Engineering 329
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Citations per field
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Citations per year

Countries citing papers authored by Raghavendra V. Kulkarni

Since Specialization
Citations

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

Fields of papers citing papers by Raghavendra V. Kulkarni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raghavendra V. Kulkarni. 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 Raghavendra V. Kulkarni. The network helps show where Raghavendra V. Kulkarni may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Raghavendra V. Kulkarni, 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 Raghavendra V. Kulkarni Line = papers co-authored together Raghavendra V. Kulkarni links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202413
2 20244
3 20240
4 202311
5 20233
6 20211
7 202035
8 20204
9 20208
10 20195
11 201658
12 201323
13 201312
14
Design and in-vitro evaluation of extended release matrix tablets ofItopride hydrochloride
20101
15 2009103
16 200914
17 200849
18 200859
19
In vitro permeation of verapamil hydrochloride from polymeric membrane systems across rat and human cadaver skin
20022
20 200223

About Raghavendra V. Kulkarni

Raghavendra V. Kulkarni is a scholar working on Pharmaceutical Science, Molecular Medicine and Geriatrics and Gerontology, having authored 101 papers that have together received 4.2k indexed citations. Recurring topics across this work include Advanced Drug Delivery Systems (31 papers), Hydrogels: synthesis, properties, applications (28 papers), Drug Solubulity and Delivery Systems (18 papers), Advancements in Transdermal Drug Delivery (15 papers), Energy Efficient Wireless Sensor Networks (12 papers), Underwater Vehicles and Communication Systems (8 papers), Indoor and Outdoor Localization Technologies (8 papers) and Polysaccharides Composition and Applications (8 papers). The work is most often cited by research in Molecular Medicine (681 citations), Pharmaceutical Science (696 citations) and Computer Networks and Communications (1.1k citations). Raghavendra V. Kulkarni has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Ganesh K. Venayagamoorthy, D. R. Sarvamangala, Biswanath Sa, Anna Förster, Srinivas Mutalik, Anjanapura V. Raghu, Kakarla Raghava Reddy, C. Mallikarjuna Setty, Nagaraj P. Shetti and G. Krishna Mohan. Their work appears in journals such as International Journal of Biological Macromolecules, Journal of Applied Polymer Science, Journal of Microbiological Methods, Current Drug Delivery and Indian Journal of Pharmaceutical Sciences.

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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