Mohit Kumar

407 citations
5 papers · 228 · 1 hit paper · h-index 3

Impact in

Papers in

Mohit Kumar

4 papers receiving 223 citations

Mohit Kumar's Hit Papers

REV2 2018 · 215 citations
2150+2+5Years since publication50100150200

Peers

Mohit Kumar
Comparison fields: 5 of 42
  • Statistical and Nonlinear Physics 112
  • Artificial Intelligence 138
  • Information Systems 80
  • Signal Processing 17
  • Computer Networks and Communications 36
Replace Disha Makhija with:
Disha Makhija United States
Timothy La Fond United States
Ayushi Dalmia India
Ralitsa Angelova Germany
Yiye Ruan United States
Shuangyong Song China
Takashi Tomokiyo United States
Yabing Yao China
Omar Shahbaz Khan Netherlands
David I. Inouye United States
Mohit Kumar relative to Disha Makhija United States Disha Makhija's profile →
Citations per field
00.5×1.5×
Disha Makhija · 1×
Citations per year

Countries citing papers authored by Mohit Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Mohit Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Mohit 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 Mohit Kumar Line = papers co-authored together Mohit Kumar links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1
REV2
Hit paper breakdown →
2018215
2 20108
3 20243
4 20242
5 20120

About Mohit Kumar

Mohit Kumar is a scholar working on Artificial Intelligence, Information Systems, Automotive Engineering, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 228 indexed citations. Recurring topics across this work include Additive Manufacturing and 3D Printing Technologies (1 paper), Spam and Phishing Detection (1 paper), Advanced Malware Detection Techniques (1 paper), Additive Manufacturing Materials and Processes (1 paper), Security and Verification in Computing (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Manufacturing Process and Optimization (1 paper) and Misinformation and Its Impacts (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (112 citations), Artificial Intelligence (138 citations), Information Systems (80 citations), Signal Processing (17 citations) and Computer Networks and Communications (36 citations). Mohit Kumar has collaborated with scholars based in India, United Arab Emirates and United States. Frequent co-authors include Disha Makhija, Christos Faloutsos, V. S. Subrahmanian, Bryan Hooi, Srijan Kumar, Poonam Singh and Abhishek Gupta. Their work appears in journals such as AIP conference proceedings and SAMRIDDHI A Journal of Physical Sciences Engineering and 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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