Supun Nakandala
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Information Systems and Management top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Arun KumarSuresh MarruMarlon PierceSudhakar PamidighantamYuhao ZhangYannis PapakonstantinouYong‐Yeol AhnNorman Makoto Su
- Topics
- Advanced Neural Network Applications (6 papers)Scientific Computing and Data Management (6 papers)Physical Activity and Health (5 papers)
- Journals
- Medicine & Science in Sports & ExerciseInternational Journal of ObesityInternational Journal of Behavioral Nutrition and Physical Activity
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Supun Nakandala
26 papers receiving 360 citations
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 123
- Computer Networks and Communications 88
- Information Systems 68
- Information Systems and Management 63
- Computer Vision and Pattern Recognition 61
Countries citing papers authored by Supun Nakandala
This map shows the geographic impact of Supun Nakandala'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 Supun Nakandala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Supun Nakandala more than expected).
Fields of papers citing papers by Supun Nakandala
This network shows the impact of papers produced by Supun Nakandala. 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 Supun Nakandala. The network helps show where Supun Nakandala may publish in the future.
Co-authorship network of co-authors of Supun Nakandala
This figure shows the co-authorship network connecting the top 25 collaborators of Supun Nakandala. A scholar is included among the top collaborators of Supun Nakandala 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 Supun Nakandala. Supun Nakandala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 5 | |
| 4 | 27 | |
| 5 | 8 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 24 | |
| 9 | 22 | |
| 10 | 42 | |
| 11 | 10 | |
| 12 | 3 | |
| 13 | 15 | |
| 14 | 19 | |
| 15 | 25 | |
| 16 | 6 | |
| 17 | 13 | |
| 18 | 2 | |
| 19 | 12 | |
| 20 | 2 |
About Supun Nakandala
Supun Nakandala is a scholar working on Information Systems and Management, Computer Vision and Pattern Recognition and Physical Therapy, Sports Therapy and Rehabilitation, having authored 26 papers that have together received 377 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Scientific Computing and Data Management (6 papers) and Physical Activity and Health (5 papers). The work is most often cited by research in Information Systems and Management (63 citations), Computational Mathematics (3 citations) and Hardware and Architecture (28 citations). Supun Nakandala has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Arun Kumar, Suresh Marru, Marlon Pierce, Sudhakar Pamidighantam, Yuhao Zhang, Yannis Papakonstantinou, Yong‐Yeol Ahn, Norman Makoto Su, Matteo Interlandi and Konstantinos Karanasos. Their work appears in journals such as Medicine & Science in Sports & Exercise, International Journal of Obesity and International Journal of Behavioral Nutrition and Physical Activity.
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.