Hongye Jin

627 citations
2 papers · 241 indexed · 1 hit paper · h-index 2
Topics
Privacy-Preserving Technologies in Data (2 papers)Advanced Neural Network Applications (1 paper)Artificial Intelligence in Healthcare and Education (1 paper)
Partner nations
United States

In The Last Decade

Hongye Jin

2 papers receiving 229 citations

Hit Papers

Harnessing the Power of LLMs in Practice: A Survey on Cha...202420262025202450100150200

Peers

Hongye Jin
Comparison fields: 5 of 73
  • Artificial Intelligence 128
  • Information Systems 41
  • Health Informatics 28
  • Computer Networks and Communications 24
  • Computer Vision and Pattern Recognition 20
Replace Shaochen Zhong with:
Shaochen Zhong United States
Yanghe Pan China
Max Hort United Kingdom
Hengyi Cai China
Doris Xin United States
Jörg Schlötterer Germany
Vivek Kumar Italy
Ambrose Azeta Nigeria
Kshitiz Aryal United States
Hongye Jin relative to Shaochen Zhong United States Shaochen Zhong's profile →
Citations per field
00.5×1.5×
Shaochen Zhong · 1×
Citations per year

Countries citing papers authored by Hongye Jin

Since Specialization
Citations

This map shows the geographic impact of Hongye 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 Hongye Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongye Jin more than expected).

Fields of papers citing papers by Hongye Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongye 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 Hongye Jin. The network helps show where Hongye Jin may publish in the future.

Co-authorship network of co-authors of Hongye Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Hongye Jin. A scholar is included among the top collaborators of Hongye 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 Hongye Jin. Hongye Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

2 of 2 papers shown
#WorkIndexed citations
1
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondbreakdown →
237
2 4

About Hongye Jin

Hongye Jin is a scholar working on Health Informatics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 2 papers that have together received 241 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (2 papers), Advanced Neural Network Applications (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (28 citations), Artificial Intelligence (128 citations) and Software (9 citations). Hongye Jin has collaborated with scholars based in United States. Frequent co-authors include Ruixiang Tang, Xia Hu, Qizhang Feng, Bing Yin, Xiaotian Han, Jingfeng Yang, Haoming Jiang, Shaochen Zhong, Curtis Wigington and Mengnan Du. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data.

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.

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