Jindong Wang
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
- Privacy-Preserving Technologies in Data
- Topic Modeling
Papers in
-
- Domain Adaptation and Few-Shot Learning 17
- Anomaly Detection Techniques and Applications 15
- Topic Modeling 13
- Machine Learning and ELM 8
- Journals
- IEEE Transactions on Knowledge and Data Engineering (4 papers)IEEE Transactions on Neural Networks and Learning Systems (3 papers)Neurocomputing (3 papers)Digital Signal Processing (3 papers)BioMed Research International (3 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Jindong Wang
211 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 209
- Health Informatics 167
- Artificial Intelligence 3.8k
- Computer Vision and Pattern Recognition 2.3k
- Signal Processing 658
- Computer Networks and Communications 873
Countries citing papers authored by Jindong Wang
This map shows the geographic impact of Jindong Wang'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 Jindong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jindong Wang more than expected).
Fields of papers citing papers by Jindong Wang
This network shows the impact of papers produced by Jindong Wang. 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 Jindong Wang. The network helps show where Jindong Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jindong Wang, 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 | 2025 | 5 | |
| 2 | 2025 | 7 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 6 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 13 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 16 | |
| 14 | 2024 | 2 | |
| 15 | 2023 | 13 | |
| 16 | 2023 | 8 | |
| 17 | 2023 | 0 | |
| 18 | Sectional normalization and recognization on the PV-Diagram of reciprocating compressor | 2015 | 2 |
| 19 | 2014 | 3 | |
| 20 | 2013 | 1 |
About Jindong Wang
Jindong Wang is a scholar working on Artificial Intelligence, Health Informatics, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 246 papers that have together received 8.4k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (17 papers), Anomaly Detection Techniques and Applications (15 papers), Topic Modeling (13 papers), Context-Aware Activity Recognition Systems (13 papers), Machine Fault Diagnosis Techniques (12 papers), Human Pose and Action Recognition (11 papers), Multimodal Machine Learning Applications (9 papers) and Machine Learning and ELM (8 papers). The work is most often cited by research in Health Informatics (167 citations), Artificial Intelligence (3.8k citations), Computer Vision and Pattern Recognition (2.3k citations), Signal Processing (658 citations) and Computer Networks and Communications (873 citations). Jindong Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yiqiang Chen, Lisha Hu, Xiaohui Peng, Shuji Hao, Philip S. Yu, Chaohui Yu, Xin Qin, Meiyu Huang, Yongchun Zhu and Fuzhen Zhuang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing, Digital Signal Processing and BioMed Research International.
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.