Sathish Kumar

69 papers receiving 1.9k citations

Sathish Kumar's Hit Papers

A review of topic modeling methods 2020 · 448 citations
4480+2+4Years since publication100200300400

Peers

Sathish Kumar
Comparison fields: 5 of 173
  • General Social Sciences 89
  • Computer Networks and Communications 511
  • Information Systems 438
  • Signal Processing 175
  • Molecular Medicine 61
Replace Florentino Fdez‐Riverola with:
Florentino Fdez‐Riverola Spain
Xiaohua Hu United States
Weizhong Zhao China
Ting Wang China
Rozita Dara Canada
Ying Zhao United States
Mário J. Silva Portugal
Peter Braun Germany
Yue Lu China
Gabriela Ochoa United Kingdom
Sathish Kumar relative to Florentino Fdez‐Riverola Spain Florentino Fdez‐Riverola's profile →
Citations per field
00.5×2×4×6×8×9.9×
Florentino Fdez‐Riverola · 1×
Citations per year

Countries citing papers authored by Sathish Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Sathish Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A review of topic modeling methods
Hit paper breakdown →
2020448
2 2016203
3 2018112
4 2016110
5 201177
6 201768
7 201867
8 201657
9 201350
10 201048
11 201740
12 201437
13 201237
14 202131
15 201531
16 201930
17 201930
18 201429
19 196026
20 202025

About Sathish Kumar

Sathish Kumar is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Molecular Biology and Signal Processing, having authored 71 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (7 papers), Bacterial Genetics and Biotechnology (6 papers), Antibiotic Resistance in Bacteria (5 papers), IoT and Edge/Fog Computing (5 papers), Advanced Malware Detection Techniques (5 papers), Network Security and Intrusion Detection (5 papers), Cloud Data Security Solutions (5 papers) and Public Relations and Crisis Communication (4 papers). The work is most often cited by research in General Social Sciences (89 citations), Computer Networks and Communications (511 citations), Information Systems (438 citations), Signal Processing (175 citations) and Molecular Medicine (61 citations). Sathish Kumar has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Harshit Srivastava, Hanna Engelberg–Kulka, Shangguang Wang, Pethuru Raj Chelliah, Ao Zhou, Fangchun Yang, Kokati Venkata Bhaskara Rao, Tao Leí, Jialei Liu and Ilana Kolodkin‐Gal. Their work appears in journals such as mBio, Die Naturwissenschaften, Wireless Personal Communications, Journal of Reliable Intelligent Environments and PLoS ONE.

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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