Sanjay Kumar

2.8k citations
80 papers · 1.9k indexed · h-index 27

Impact in

Papers in

Sanjay Kumar

76 papers receiving 1.8k citations

Peers

Sanjay Kumar
Comparison fields: 5 of 120
  • Management Science and Operations Research 1.2k
  • Statistics and Probability 263
  • Signal Processing 239
  • Artificial Intelligence 576
  • Computational Theory and Mathematics 233
Replace Chonghui Guo with:
Chonghui Guo China
Hongjun Wang China
Rafik Aziz Aliev Azerbaijan
Thomas A. Runkler Germany
Emilio Carrizosa Spain
Piero P. Bonissone United States
Yinghua Shen China
Junyi Chai Hong Kong
Liguo Fei China
Antonio González Spain
Sanjay Kumar relative to Chonghui Guo China Chonghui Guo's profile →
Citations per field
00.5×1.5×2.5×
Chonghui Guo · 1×
Citations per year

Countries citing papers authored by Sanjay Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Sanjay Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20242
4 20243
5 20235
6 202311
7 20239
8 20233
9 20226
10 202046
11 20193
12 201915
13 20173
14 20174
15 201641
16 201517
17
Recent Trends In Industrial And Other Engineering Applications Of Non Destructive Testing: A Review
201314
18 201233
19
Need of library training programe and importance of information sources for the veterinary scientists.
20091
20 19992

About Sanjay Kumar

Sanjay Kumar is a scholar working on Management Science and Operations Research, Statistics and Probability, Signal Processing, Artificial Intelligence and Control and Systems Engineering, having authored 80 papers that have together received 1.9k indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (22 papers), Multi-Criteria Decision Making (19 papers), Fuzzy Systems and Optimization (15 papers), Fuzzy Logic and Control Systems (15 papers), Optimization and Mathematical Programming (12 papers), Forecasting Techniques and Applications (11 papers), Rough Sets and Fuzzy Logic (10 papers) and Complex Systems and Time Series Analysis (10 papers). The work is most often cited by research in Management Science and Operations Research (1.2k citations), Statistics and Probability (263 citations), Signal Processing (239 citations), Artificial Intelligence (576 citations) and Computational Theory and Mathematics (233 citations). Sanjay Kumar has collaborated with scholars based in India, Egypt and Germany. Frequent co-authors include Deepa Joshi, H. Hannah Inbarani, Bhagawati Prasad Joshi, Krishna Kumar Gupta, Manish Pant, Reshma Rastogi, Ismat Beg, Ahmad Taher Azar, P. Balasubramaniam and Abid Haleem. Their work appears in journals such as Granular Computing, Expert Systems with Applications, Information Sciences, European Journal of Operational Research and Neural Computing and Applications.

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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