Feifei Jin

1.6k citations
63 papers · 1.3k · h-index 21

Impact in

Papers in

Feifei Jin

60 papers receiving 1.2k citations

Peers

Feifei Jin
Comparison fields: 5 of 89
  • Management Science and Operations Research 1.0k
  • Statistics and Probability 187
  • Computational Theory and Mathematics 260
  • Artificial Intelligence 454
  • Control and Systems Engineering 270
Replace Hong‐gang Peng with:
Hong‐gang Peng China
Fei Teng China
Sumin Yu China
Jawad Ali Pakistan
Zhiliang Ren China
Bahram Farhadinia Iran
Zhengmin Liu China
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Feifei Jin relative to Hong‐gang Peng China Hong‐gang Peng's profile →
Citations per field
00.5×10×20×29×
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Citations per year

Countries citing papers authored by Feifei Jin

Since Specialization
Citations

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

Fields of papers citing papers by Feifei Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Feifei Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Feifei Jin Line = papers co-authored together Feifei Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201496
2 202191
3 202174
4 202365
5 201664
6 202257
7 201654
8 202050
9 202240
10 202038
11 201635
12 201734
13 201733
14 201530
15 202130
16 201830
17 201730
18 201825
19 201522
20 201821

About Feifei Jin

Feifei Jin is a scholar working on Management Science and Operations Research, Artificial Intelligence, Control and Systems Engineering, Computational Theory and Mathematics and Statistics and Probability, having authored 63 papers that have together received 1.3k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (53 papers), Optimization and Mathematical Programming (19 papers), Rough Sets and Fuzzy Logic (14 papers), Cognitive Science and Mapping (12 papers), Bayesian Modeling and Causal Inference (9 papers), Fuzzy Systems and Optimization (7 papers), Efficiency Analysis Using DEA (7 papers) and Metaheuristic Optimization Algorithms Research (5 papers). The work is most often cited by research in Management Science and Operations Research (1.0k citations), Statistics and Probability (187 citations), Computational Theory and Mathematics (260 citations), Artificial Intelligence (454 citations) and Control and Systems Engineering (270 citations). Feifei Jin has collaborated with scholars based in China, United States and India. Frequent co-authors include Huayou Chen, Jinpei Liu, Ligang Zhou, Zhiwei Ni, Lidan Pei, Yaping Li, Luis Martı́nez, Xuhui Zhu, Zhifu Tao and Reza Langari. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Engineering Applications of Artificial Intelligence, Computers & Industrial Engineering, Applied Intelligence and Knowledge-Based Systems.

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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