Jia Yao
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Molecular Biology
- Ocean Engineering
- Information Systems
- Co-authors
- Manoranjan DashHua LiuMehul MotaniP. M. AdlerF. KalaydjianPeter FrykmanJean‐François ThovertE.J. Dodson
- Topics
- Machine Learning in Healthcare (6 papers)AI in cancer detection (3 papers)Phonocardiography and Auscultation Techniques (3 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionHealth Information Management
- Journals
- Journal of Colloid and Interface ScienceExpert Systems with ApplicationsBiochemical Society Transactions
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Jia Yao
22 papers receiving 308 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 135
- Computer Vision and Pattern Recognition 78
- Molecular Biology 47
- Ocean Engineering 35
- Information Systems 27
Countries citing papers authored by Jia Yao
This map shows the geographic impact of Jia Yao'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 Jia Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia Yao more than expected).
Fields of papers citing papers by Jia Yao
This network shows the impact of papers produced by Jia Yao. 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 Jia Yao. The network helps show where Jia Yao may publish in the future.
Co-authorship network of co-authors of Jia Yao
This figure shows the co-authorship network connecting the top 25 collaborators of Jia Yao. A scholar is included among the top collaborators of Jia Yao 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 Jia Yao. Jia Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 14 | |
| 6 | 18 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 14 | |
| 11 | 10 | |
| 12 | 2 | |
| 13 | 20 | |
| 14 | 12 | |
| 15 | Deep Spatio-Temporal Feature Learning using Autoencoders | 1 |
| 16 | 17 | |
| 17 | 21 | |
| 18 | 10 | |
| 19 | 5 | |
| 20 | 41 |
About Jia Yao
Jia Yao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management, having authored 23 papers that have together received 334 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), AI in cancer detection (3 papers) and Phonocardiography and Auscultation Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (135 citations), Computer Vision and Pattern Recognition (78 citations) and Health Information Management (17 citations). Jia Yao has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Manoranjan Dash, Hua Liu, Mehul Motani, P. M. Adler, F. Kalaydjian, Peter Frykman, Jean‐François Thovert, E.J. Dodson, Keith S. Wilson and M. M. Woolfson. Their work appears in journals such as Journal of Colloid and Interface Science, Expert Systems with Applications and Biochemical Society Transactions.
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.