Hao Jin
Impact in
- Information Systems top 5%
- Blockchain Technology Applications and Security
- Cloud Data Security Solutions
- Internet of Things and AI
-
- Artificial Intelligence in Healthcare and Education
Papers in
-
- Blockchain Technology Applications and Security 5
- Cloud Data Security Solutions 3
-
- Cryptography and Data Security 4
- Privacy-Preserving Technologies in Data 3
- Security and Verification in Computing 2
- Co-authors
- Peilong Li (4 shared papers)Yan Luo (4 shared papers)Jomol Mathew (3 shared papers)Hong Jiang (2 shared papers)Ke Zhou (2 shared papers)Yu Cao (2 shared papers)Chunhua Li (1 shared paper)Chunyang Hu (1 shared paper)
- Journals
- IEEE Systems Journal (1 paper)IEEE Access (1 paper)Future Generation Computer Systems (1 paper)IEEE Transactions on Cloud Computing (1 paper)SSRN Electronic Journal (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Hao Jin
9 papers receiving 302 citations
Peers
Comparison fields: 5 of 59
- Information Systems 252
- Health Informatics 11
- Artificial Intelligence 181
- Computer Networks and Communications 103
- Health Information Management 13
Countries citing papers authored by Hao Jin
This map shows the geographic impact of Hao Jin'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 Hao Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Jin more than expected).
Fields of papers citing papers by Hao Jin
This network shows the impact of papers produced by Hao Jin. 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 Hao Jin. The network helps show where Hao Jin may publish in the future.
Co-authors
The 22 scholars most cited alongside Hao Jin, 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 | 2019 | 174 | |
| 2 | 2016 | 64 | |
| 3 | 2019 | 32 | |
| 4 | 2016 | 29 | |
| 5 | 2019 | 12 | |
| 6 | 2019 | 7 | |
| 7 | 2017 | 1 | |
| 8 | 2012 | 1 | |
| 9 | 2022 | 1 |
About Hao Jin
Hao Jin is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science and Signal Processing, having authored 9 papers that have together received 321 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (5 papers), Cryptography and Data Security (4 papers), Privacy-Preserving Technologies in Data (3 papers), Cloud Data Security Solutions (3 papers), Security and Verification in Computing (2 papers), IoT and Edge/Fog Computing (2 papers), Advanced Data Storage Technologies (1 paper) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Information Systems (252 citations), Health Informatics (11 citations), Artificial Intelligence (181 citations), Computer Networks and Communications (103 citations) and Health Information Management (13 citations). Hao Jin has collaborated with scholars based in China and United States. Frequent co-authors include Peilong Li, Yan Luo, Jomol Mathew, Hong Jiang, Ke Zhou, Yu Cao, Chunhua Li, Chunyang Hu, Yunsheng Ma and Xinfang Zhang. Their work appears in journals such as IEEE Systems Journal, IEEE Access, Future Generation Computer Systems, IEEE Transactions on Cloud Computing and SSRN Electronic Journal.
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.