Rong Jin
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computational Mechanics
- Signal Processing top 10%
- Co-authors
- Zhi‐Hua ZhouMiao XuLuo SiShaili JainJinfeng YiAnil K. JainMehrdad MahdaviXiaohong Chen
- Topics
- Organometallic Complex Synthesis and Catalysis (13 papers)Synthesis and characterization of novel inorganic/organometallic compounds (9 papers)Organoboron and organosilicon chemistry (6 papers)
- Cited by
- Computational MathematicsComputer Science ApplicationsComputer Vision and Pattern Recognition
- Partner nations
- United StatesChinaMexico
In The Last Decade
Rong Jin
39 papers receiving 396 citations
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 166
- Computer Vision and Pattern Recognition 125
- Information Systems 82
- Computational Mechanics 60
- Signal Processing 49
Countries citing papers authored by Rong Jin
This map shows the geographic impact of Rong 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 Rong Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rong Jin more than expected).
Fields of papers citing papers by Rong Jin
This network shows the impact of papers produced by Rong 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 Rong Jin. The network helps show where Rong Jin may publish in the future.
Co-authorship network of co-authors of Rong Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Rong Jin. A scholar is included among the top collaborators of Rong 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 Rong Jin. Rong 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 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 7 | |
| 13 | Stochastic Convex Optimization with Multiple Objectives | 17 |
| 14 | Speedup Matrix Completion with Side Information: Application to Multi-Label Learning | 148 |
| 15 | On Theoretical Analysis of Distributed Stochastic Dual Coordinate Ascent. | 2 |
| 16 | Mixed Optimization for Smooth Functions | 10 |
| 17 | Crowdclustering with sparse pairwise labels: A matrix completion approach | 28 |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 5 |
About Rong Jin
Rong Jin is a scholar working on Process Chemistry and Technology, Inorganic Chemistry and Human-Computer Interaction, having authored 45 papers that have together received 409 indexed citations. Recurring topics across this work include Organometallic Complex Synthesis and Catalysis (13 papers), Synthesis and characterization of novel inorganic/organometallic compounds (9 papers) and Organoboron and organosilicon chemistry (6 papers). The work is most often cited by research in Computational Mathematics (9 citations), Computer Science Applications (49 citations) and Computer Vision and Pattern Recognition (125 citations). Rong Jin has collaborated with scholars based in United States, China and Mexico. Frequent co-authors include Zhi‐Hua Zhou, Miao Xu, Luo Si, Shaili Jain, Jinfeng Yi, Anil K. Jain, Mehrdad Mahdavi, Xiaohong Chen, Yaoming Xie and Tianbao Yang. Their work appears in journals such as Applied Surface Science, RSC Advances and Medicine.
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.