Jun Zhao
Impact in
- Artificial Intelligence top 0.05%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Sentiment Analysis and Opinion Mining
- Advanced Graph Neural Networks
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- Data Quality and Management
Papers in
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- Topic Modeling 121
- Natural Language Processing Techniques 83
- Advanced Text Analysis Techniques 24
- Text and Document Classification Technologies 20
- Advanced Graph Neural Networks 18
- Sentiment Analysis and Opinion Mining 16
- Semantic Web and Ontologies 11
Jun Zhao
161 papers receiving 8.3k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Artificial Intelligence 7.6k
- Management Science and Operations Research 910
- Information Systems 1.5k
- Computer Vision and Pattern Recognition 780
- General Social Sciences 71
Countries citing papers authored by Jun Zhao
This map shows the geographic impact of Jun Zhao'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 Jun Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Zhao more than expected).
Fields of papers citing papers by Jun Zhao
This network shows the impact of papers produced by Jun Zhao. 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 Jun Zhao. The network helps show where Jun Zhao may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Zhao, 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 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 27 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 0 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 4 | |
| 10 | 2021 | 42 | |
| 11 | 2021 | 38 | |
| 12 | 2021 | 7 | |
| 13 | 2020 | 4 | |
| 14 | 2019 | 14 | |
| 15 | 2019 | 98 | |
| 16 | 2018 | 96 | |
| 17 | Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks Hit paper breakdown → | 2015 | 548 |
| 18 | Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks Hit paper breakdown → | 2015 | 680 |
| 19 | New biological species of Armillaria in China | 2000 | 5 |
| 20 | Mating relationships between Chinese biological species and North American species of Armillaria. | 1999 | 4 |
About Jun Zhao
Jun Zhao is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Vision and Pattern Recognition and Pharmacology, having authored 177 papers that have together received 8.8k indexed citations. Recurring topics across this work include Topic Modeling (121 papers), Natural Language Processing Techniques (83 papers), Advanced Text Analysis Techniques (24 papers), Text and Document Classification Technologies (20 papers), Advanced Graph Neural Networks (18 papers), Sentiment Analysis and Opinion Mining (16 papers), Multimodal Machine Learning Applications (14 papers) and Semantic Web and Ontologies (11 papers). The work is most often cited by research in Artificial Intelligence (7.6k citations), Management Science and Operations Research (910 citations), Information Systems (1.5k citations), Computer Vision and Pattern Recognition (780 citations) and General Social Sciences (71 citations). Jun Zhao has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Kang Liu, Siwei Lai, Liheng Xu, Daojian Zeng, Yubo Chen, Yubo Chen, Guangyou Zhou, Shizhu He, Shizhu He and Xianpei Han. Their work appears in journals such as IEEE Intelligent Systems, Progress in Organic Coatings, BMC Medical Informatics and Decision Making, Journal of the Optical Society of America B and Scientific Reports.
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.