Divine T. Ndumu

17 papers receiving 477 citations

Peers

Divine T. Ndumu
Comparison fields: 5 of 65
  • Artificial Intelligence 374
  • Computer Networks and Communications 242
  • Information Systems 145
  • Management Information Systems 76
  • Management Science and Operations Research 53
Replace Dominic Greenwood with:
Dominic Greenwood United Kingdom
Giovanni Caire Italy
Everton Cavalcante Brazil
Jorge J. Gómez-Sanz Spain
Kutluhan Erol United States
A. Taleb-Bendiab United Kingdom
Fereidoon Shams Aliee Iran
Philippe Lalanda France
Amy Apon United States
Yuhong Yan Canada
Divine T. Ndumu relative to Dominic Greenwood United Kingdom Dominic Greenwood's profile →
Citations per field
00.5×
Dominic Greenwood · 1×
Citations per year

Countries citing papers authored by Divine T. Ndumu

Since Specialization
Citations

This map shows the geographic impact of Divine T. Ndumu'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 Divine T. Ndumu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Divine T. Ndumu more than expected).

Fields of papers citing papers by Divine T. Ndumu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Divine T. Ndumu. 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 Divine T. Ndumu. The network helps show where Divine T. Ndumu may publish in the future.

Co-authorship network of co-authors of Divine T. Ndumu

This figure shows the co-authorship network connecting the top 25 collaborators of Divine T. Ndumu. A scholar is included among the top collaborators of Divine T. Ndumu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Divine T. Ndumu. Divine T. Ndumu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1
ZEUS: A Collaborative Agents Toolkit
3
2 8
3 113
4 134
5
Distributed Genetic Programming with mobile agents
0
6 31
7 51
8 24
9 44
10 17
11 61
12 3
13 24
14 29
15 1
16 28
17 2
18 3
19 3

About Divine T. Ndumu

Divine T. Ndumu is a scholar working on Computer Networks and Communications, Artificial Intelligence and Industrial and Manufacturing Engineering, having authored 19 papers that have together received 579 indexed citations. Recurring topics across this work include Multi-Agent Systems and Negotiation (10 papers), Mobile Agent-Based Network Management (9 papers) and Semantic Web and Ontologies (5 papers). The work is most often cited by research in Artificial Intelligence (374 citations), Computer Networks and Communications (242 citations) and Management Information Systems (76 citations). Divine T. Ndumu has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Hyacinth S. Nwana, Jaron C. Collis, Philippe De Wilde, J.P. Roberts, Robert Ghanea‐Hercock, B.A. Izzuddin, David L. Smith and Ben Azvine. Their work appears in journals such as International Journal of Machine Tools and Manufacture, Knowledge-Based Systems and Computer-Aided Civil and Infrastructure Engineering.

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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