Susan Elias
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Co-authors
- K. GayathriK. S. EaswarakumarBalaraman RavindranSrinivasan RajagopalanRichard ChbeirSaswati MukherjeeLisa Sara MathewXianwen Gao
- Topics
- IoT and Edge/Fog Computing (7 papers)Context-Aware Activity Recognition Systems (6 papers)Human Pose and Action Recognition (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Science ApplicationsArtificial Intelligence
- Partner nations
- IndiaUnited StatesFrance
In The Last Decade
Susan Elias
30 papers receiving 309 citations
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 143
- Artificial Intelligence 107
- Computer Networks and Communications 74
- Electrical and Electronic Engineering 59
- Biomedical Engineering 52
Countries citing papers authored by Susan Elias
This map shows the geographic impact of Susan Elias'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 Susan Elias with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Susan Elias more than expected).
Fields of papers citing papers by Susan Elias
This network shows the impact of papers produced by Susan Elias. 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 Susan Elias. The network helps show where Susan Elias may publish in the future.
Co-authorship network of co-authors of Susan Elias
This figure shows the co-authorship network connecting the top 25 collaborators of Susan Elias. A scholar is included among the top collaborators of Susan Elias 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 Susan Elias. Susan Elias 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 | 1 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 12 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 56 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 6 | |
| 13 | 7 | |
| 14 | 15 | |
| 15 | 1 | |
| 16 | 10 | |
| 17 | 14 | |
| 18 | 23 | |
| 19 | 0 | |
| 20 | 6 |
About Susan Elias
Susan Elias is a scholar working on Computer Science Applications, Health Information Management and Human-Computer Interaction, having authored 35 papers that have together received 322 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (7 papers), Context-Aware Activity Recognition Systems (6 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (143 citations), Computer Science Applications (23 citations) and Artificial Intelligence (107 citations). Susan Elias has collaborated with scholars based in India, United States and France. Frequent co-authors include K. Gayathri, K. S. Easwarakumar, Balaraman Ravindran, Srinivasan Rajagopalan, Richard Chbeir, Saswati Mukherjee, Lisa Sara Mathew, Xianwen Gao, Li Liu and Wenxin Liu. Their work appears in journals such as IEEE Access, Knowledge-Based Systems and Pattern Recognition Letters.
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.