Jinhao Jiang
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Advanced Graph Neural Networks
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Bayesian Modeling and Causal Inference
Papers in
-
- Topic Modeling 8
- Natural Language Processing Techniques 7
- Semantic Web and Ontologies 3
- Advanced Graph Neural Networks 3
- AI-based Problem Solving and Planning 1
- Text and Document Classification Technologies 1
-
- Multimodal Machine Learning Applications 1
- Co-authors
- Ji-Rong Wen (9 shared papers)Wayne Xin Zhao (8 shared papers)Gaole He (3 shared papers)Jing Jiang (2 shared papers)Yunshi Lan (2 shared papers)Kun Zhou (5 shared papers)Zican Dong (1 shared paper)Tianyi Tang (1 shared paper)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (1 paper)Signal Image and Video Processing (1 paper)
- Partner nations
- ChinaSingaporeNetherlands
In The Last Decade
Jinhao Jiang
7 papers receiving 229 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 206
- Health Informatics 8
- Management Science and Operations Research 24
- Information Systems 37
- Computer Vision and Pattern Recognition 32
Countries citing papers authored by Jinhao Jiang
This map shows the geographic impact of Jinhao Jiang'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 Jinhao Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinhao Jiang more than expected).
Fields of papers citing papers by Jinhao Jiang
This network shows the impact of papers produced by Jinhao Jiang. 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 Jinhao Jiang. The network helps show where Jinhao Jiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jinhao Jiang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 77 | |
| 2 | 2021 | 76 | |
| 3 | 2022 | 51 | |
| 4 | 2021 | 18 | |
| 5 | 2023 | 8 | |
| 6 | 2022 | 4 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 | |
| 9 | 2025 | 0 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Jinhao Jiang
Jinhao Jiang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Infectious Diseases and Organic Chemistry, having authored 12 papers that have together received 235 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers), Semantic Web and Ontologies (3 papers), Advanced Graph Neural Networks (3 papers), Multimodal Machine Learning Applications (1 paper), AI-based Problem Solving and Planning (1 paper), Text and Document Classification Technologies (1 paper) and Nanomaterials and Printing Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (206 citations), Health Informatics (8 citations), Management Science and Operations Research (24 citations), Information Systems (37 citations) and Computer Vision and Pattern Recognition (32 citations). Jinhao Jiang has collaborated with scholars based in China, Singapore and Netherlands. Frequent co-authors include Ji-Rong Wen, Wayne Xin Zhao, Gaole He, Jing Jiang, Yunshi Lan, Kun Zhou, Zican Dong, Tianyi Tang, Junyi Li and Zhipeng Chen. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering and Signal Image and Video Processing.
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.