Haifeng Jin
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Signal Processing top 10%
- Topics
- Machine Learning and Data Classification (6 papers)Advanced Neural Network Applications (4 papers)Network Security and Intrusion Detection (4 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsGastrointestinal EndoscopyFrontiers in Oncology
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Haifeng Jin
22 papers receiving 682 citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Artificial Intelligence 372
- Computer Vision and Pattern Recognition 168
- Computer Networks and Communications 68
- Electrical and Electronic Engineering 64
- Signal Processing 63
Countries citing papers authored by Haifeng Jin
This map shows the geographic impact of Haifeng 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 Haifeng Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haifeng Jin more than expected).
Fields of papers citing papers by Haifeng Jin
This network shows the impact of papers produced by Haifeng 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 Haifeng Jin. The network helps show where Haifeng Jin may publish in the future.
Co-authorship network of co-authors of Haifeng Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Haifeng Jin. A scholar is included among the top collaborators of Haifeng Jin 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 Haifeng Jin. Haifeng Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 10 | |
| 8 | 13 | |
| 9 | Efficient Neural Architecture Search for Automated Deep Learning | 0 |
| 10 | 12 | |
| 11 | 10 | |
| 12 | 9 | |
| 13 | Auto-Keras: An Efficient Neural Architecture Search Systembreakdown → | 517 |
| 14 | Efficient Neural Architecture Search with Network Morphism | 29 |
| 15 | Auto-Keras: Efficient Neural Architecture Search with Network Morphism | 28 |
| 16 | 2 | |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 20 | |
| 20 | 2 |
About Haifeng Jin
Haifeng Jin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 27 papers that have together received 708 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (6 papers), Advanced Neural Network Applications (4 papers) and Network Security and Intrusion Detection (4 papers). The work is most often cited by research in Artificial Intelligence (372 citations), Computer Vision and Pattern Recognition (168 citations) and Health Informatics (8 citations). Haifeng Jin has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Qingquan Song, Xia Hu, Hu Xia, Baojiang Cui, Kaixiong Zhou, Zheli Liu, Yuening Li, Daochen Zha, Zirui Liu and Haifeng Chen. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Gastrointestinal Endoscopy and Frontiers in Oncology.
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.