Kun Yi
Impact in
-
- Time Series Analysis and Forecasting
-
- Image and Video Quality Assessment
- Advanced Neural Network Applications
Papers in
-
- Time Series Analysis and Forecasting 9
-
- Anomaly Detection Techniques and Applications 4
- Natural Language Processing Techniques 3
- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- Qi Zhang (8 shared papers)Hui He (7 shared papers)Zhendong Niu (6 shared papers)Longbing Cao (3 shared papers)Lifeng Sun (5 shared papers)Zhi Wang (5 shared papers)Yixiao Ge (3 shared papers)Ying Shan (3 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (2 papers)Information Fusion (1 paper)Environmental Health Perspectives (1 paper)Information Sciences (1 paper)ACM Transactions on Information Systems (1 paper)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Kun Yi
24 papers receiving 214 citations
Peers
Comparison fields: 5 of 65
- Signal Processing 42
- Computer Vision and Pattern Recognition 48
- Artificial Intelligence 61
- Management Science and Operations Research 17
- Health, Toxicology and Mutagenesis 17
Countries citing papers authored by Kun Yi
This map shows the geographic impact of Kun Yi'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 Kun Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Yi more than expected).
Fields of papers citing papers by Kun Yi
This network shows the impact of papers produced by Kun Yi. 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 Kun Yi. The network helps show where Kun Yi may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Yi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 31 | |
| 2 | 2022 | 29 | |
| 3 | 2024 | 23 | |
| 4 | 2022 | 22 | |
| 5 | 2024 | 16 | |
| 6 | 2018 | 12 | |
| 7 | 2023 | 12 | |
| 8 | 2025 | 11 | |
| 9 | 2017 | 9 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 7 | |
| 12 | 2022 | 6 | |
| 13 | 2020 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2023 | 5 | |
| 16 | 2017 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2025 | 2 | |
| 19 | 2020 | 2 | |
| 20 | 2025 | 2 |
About Kun Yi
Kun Yi is a scholar working on Signal Processing, Artificial Intelligence, Management Science and Operations Research, Building and Construction and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 220 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (9 papers), Stock Market Forecasting Methods (4 papers), Anomaly Detection Techniques and Applications (4 papers), Natural Language Processing Techniques (3 papers), Traffic Prediction and Management Techniques (3 papers), Forecasting Techniques and Applications (3 papers), Complex Systems and Time Series Analysis (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Signal Processing (42 citations), Computer Vision and Pattern Recognition (48 citations), Artificial Intelligence (61 citations), Management Science and Operations Research (17 citations) and Health, Toxicology and Mutagenesis (17 citations). Kun Yi has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Qi Zhang, Hui He, Zhendong Niu, Longbing Cao, Lifeng Sun, Zhi Wang, Yixiao Ge, Ying Shan, Jiangchuan Liu and Kaize Shi. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Information Fusion, Environmental Health Perspectives, Information Sciences and ACM Transactions on Information 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.