RN Uma

511 citations
11 papers · 387 · h-index 5

Impact in

Papers in

RN Uma

9 papers receiving 367 citations

Peers

RN Uma
Comparison fields: 5 of 33
  • Computer Networks and Communications 317
  • Computer Vision and Pattern Recognition 87
  • Hardware and Architecture 26
  • Information Systems 79
  • Electrical and Electronic Engineering 129
Replace Bangbang Ren with:
Bangbang Ren China
Jaime Galán–Jiménez Spain
Csaba Király Italy
Yajuan Qin China
Asma Elmangoush Germany
Philippe Bertin France
Runqun Xiong China
Mateus Augusto Silva Santos Brazil
Jiagang Liu China
Adrien Lèbre France
RN Uma relative to Bangbang Ren China Bangbang Ren's profile →
Citations per field
00.5×10×14×
Bangbang Ren · 1×
Citations per year

Countries citing papers authored by RN Uma

Since Specialization
Citations

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

Fields of papers citing papers by RN Uma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside RN Uma, 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 RN Uma Line = papers co-authored together RN Uma links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2016198
2 200682
3 201348
4 201242
5 202110
6 20064
7 20251
8 20101
9 20121
10 20030
11 20040

About RN Uma

RN Uma is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 387 indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (4 papers), Mobile Ad Hoc Networks (4 papers), Optimization and Search Problems (3 papers), Cloud Computing and Resource Management (2 papers), Wireless Communication Security Techniques (1 paper), Green IT and Sustainability (1 paper), Statistics Education and Methodologies (1 paper) and IoT and Edge/Fog Computing (1 paper). The work is most often cited by research in Computer Networks and Communications (317 citations), Computer Vision and Pattern Recognition (87 citations), Hardware and Architecture (26 citations), Information Systems (79 citations) and Electrical and Electronic Engineering (129 citations). RN Uma has collaborated with scholars based in United States, China and Slovenia. Frequent co-authors include K. P. Subbalakshmi, R. Chandramouli, Donghyun Kim, Weili Wu, Alade Tokuta, Wei Wang, Wei Wang, D. Elumalai, Joel Wein and David P. Williamson. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Transactions on Cloud Computing, Theoretical Computer Science, ACM Transactions on Information and System Security and ACADEMICIA An International Multidisciplinary Research Journal.

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.

Explore authors with similar magnitude of impact