Tom Wanyama
- Industrial and Manufacturing Engineering top 5%
- Information Systems top 10%
- Artificial Intelligence
- Control and Systems Engineering
- Computer Networks and Communications
- Topics
- Experimental Learning in Engineering (8 papers)Software Engineering Research (6 papers)Advanced Software Engineering Methodologies (6 papers)
- Journals
- Journal of Network and Computer ApplicationsProcedia ManufacturingInternational journal of engineering education
- Partner nations
- CanadaChinaUnited States
In The Last Decade
Tom Wanyama
25 papers receiving 250 citations
Peers
Comparison fields: 5 of 59
- Industrial and Manufacturing Engineering 102
- Information Systems 64
- Artificial Intelligence 63
- Control and Systems Engineering 42
- Computer Networks and Communications 29
Countries citing papers authored by Tom Wanyama
This map shows the geographic impact of Tom Wanyama'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 Tom Wanyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Wanyama more than expected).
Fields of papers citing papers by Tom Wanyama
This network shows the impact of papers produced by Tom Wanyama. 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 Tom Wanyama. The network helps show where Tom Wanyama may publish in the future.
Co-authorship network of co-authors of Tom Wanyama
This figure shows the co-authorship network connecting the top 25 collaborators of Tom Wanyama. A scholar is included among the top collaborators of Tom Wanyama 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 Tom Wanyama. Tom Wanyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 6 | |
| 4 | Practice-Intensive Learning: An effective approach to enhance the fundamental skills of PLC beginners | 1 |
| 5 | 63 | |
| 6 | Using industry 4.0 technologies to support teaching andlearning | 8 |
| 7 | 10 | |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | AN EMPIRICAL STUDY TO COMPARE THREE METHODS FOR SELECTING COTS SOFTWARE COMPONENTS | 9 |
| 13 | 1 | |
| 14 | 25 | |
| 15 | 0 | |
| 16 | 18 | |
| 17 | 4 | |
| 18 | 9 | |
| 19 | 7 | |
| 20 | Agent-Based Commercial Off-The-Shelf Software Components Evaluation Method | 1 |
About Tom Wanyama
Tom Wanyama is a scholar working on Media Technology, Industrial and Manufacturing Engineering and Artificial Intelligence, having authored 26 papers that have together received 272 indexed citations. Recurring topics across this work include Experimental Learning in Engineering (8 papers), Software Engineering Research (6 papers) and Advanced Software Engineering Methodologies (6 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (102 citations), Software (11 citations) and Information Systems (64 citations). Tom Wanyama has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Ishwar Singh, Behrouz H. Far, Dan Centea, Zhen Gao, Weiran Shen and Brian W. Baetz. Their work appears in journals such as Journal of Network and Computer Applications, Procedia Manufacturing and International journal of engineering education.
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.