Jaydeep Karandikar

1.1k citations
46 papers · 821 · h-index 15

Impact in

Papers in

Jaydeep Karandikar

43 papers receiving 793 citations

Peers

Jaydeep Karandikar
Comparison fields: 5 of 67
  • Industrial and Manufacturing Engineering 297
  • Mechanical Engineering 653
  • Statistics, Probability and Uncertainty 55
  • Medical Laboratory Technology 9
  • Electrical and Electronic Engineering 306
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Tongshun Liu China
Xinyong Mao China
Pierre Dehombreux Belgium
Xingwei Xu China
Songping He China
P.M. Lister United Kingdom
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Citations per field
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Tongshun Liu · 1×
Citations per year

Countries citing papers authored by Jaydeep Karandikar

Since Specialization
Citations

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

Fields of papers citing papers by Jaydeep Karandikar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016180
2 201497
3 201358
4 201347
5 201243
6 202039
7 202138
8 201128
9 202227
10 202321
11 201921
12 201417
13 201217
14 202017
15 201416
16 201313
17 199813
18 202112
19 201411
20 201410

About Jaydeep Karandikar

Jaydeep Karandikar is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering, Electrical and Electronic Engineering, Biomedical Engineering and Statistics, Probability and Uncertainty, having authored 46 papers that have together received 821 indexed citations. Recurring topics across this work include Advanced machining processes and optimization (30 papers), Manufacturing Process and Optimization (19 papers), Advanced Measurement and Metrology Techniques (15 papers), Advanced Surface Polishing Techniques (7 papers), Advanced Machining and Optimization Techniques (7 papers), Optimal Experimental Design Methods (5 papers), Probabilistic and Robust Engineering Design (5 papers) and Additive Manufacturing Materials and Processes (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (297 citations), Mechanical Engineering (653 citations), Statistics, Probability and Uncertainty (55 citations), Medical Laboratory Technology (9 citations) and Electrical and Electronic Engineering (306 citations). Jaydeep Karandikar has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include Tony L. Schmitz, Ali E. Abbas, Scott Smith, Thomas R. Kurfess, Mohamed El Mansori, Chandra Nath, Sam Turner, Nam Ho Kim, Andrew Honeycutt and Thomas Feldhausen. Their work appears in journals such as Manufacturing Letters, Journal of Manufacturing Science and Engineering, Journal of Manufacturing Processes, Precision Engineering and The International Journal of Advanced Manufacturing Technology.

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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