Jun Feng

2.2k total citations · 1 hit paper
86 papers, 1.3k citations indexed

About

Jun Feng is a scholar working on Artificial Intelligence, Signal Processing and Environmental Engineering. According to data from OpenAlex, Jun Feng has authored 86 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 24 papers in Signal Processing and 20 papers in Environmental Engineering. Recurrent topics in Jun Feng's work include Hydrological Forecasting Using AI (19 papers), Data Management and Algorithms (19 papers) and Hydrology and Watershed Management Studies (14 papers). Jun Feng is often cited by papers focused on Hydrological Forecasting Using AI (19 papers), Data Management and Algorithms (19 papers) and Hydrology and Watershed Management Studies (14 papers). Jun Feng collaborates with scholars based in China, Japan and Malaysia. Jun Feng's co-authors include Yuelong Zhu, Yukai Ding, Yirui Wu, Pengcheng Zhang, Xiaoyan Zhu, Minlie Huang, Jiamin Lu, Yang Yang, Zhao Li and Jidong Ge and has published in prestigious journals such as Journal of Hydrology, Optics Express and Expert Systems with Applications.

In The Last Decade

Jun Feng

77 papers receiving 1.2k citations

Hit Papers

Interpretable spatio-temporal attention LSTM model for fl... 2020 2026 2022 2024 2020 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Interpretable spatio-temporal attention LSTM model for flood forecasting
    2020 286 citations Yuelong Zhu, Jun Feng et al. Neurocomputing profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jun Feng China 17 444 357 266 255 209 86 1.3k
Chuan Luo China 23 499 1.1× 97 0.3× 146 0.5× 147 0.6× 449 2.1× 100 1.6k
N. Karunanithi United States 12 239 0.5× 446 1.2× 185 0.7× 317 1.2× 183 0.9× 19 1.6k
Maheshwari Prasad Singh India 18 268 0.6× 178 0.5× 79 0.3× 79 0.3× 336 1.6× 109 1.2k
Raquel Martínez‐España Spain 18 268 0.6× 159 0.4× 74 0.3× 102 0.4× 95 0.5× 80 938
Wen Luo China 22 175 0.4× 213 0.6× 155 0.6× 43 0.2× 299 1.4× 96 1.6k
Xiuwen Yi China 15 311 0.7× 547 1.5× 130 0.5× 39 0.2× 77 0.4× 23 2.2k
Yue‐Shan Chang Taiwan 17 244 0.5× 424 1.2× 97 0.4× 32 0.1× 339 1.6× 87 1.2k
Eiji Mizutani Taiwan 10 727 1.6× 153 0.4× 59 0.2× 101 0.4× 97 0.5× 48 1.6k
Feng Xu China 23 253 0.6× 133 0.4× 106 0.4× 60 0.2× 209 1.0× 121 1.7k
Yong-Hyuk Kim South Korea 16 404 0.9× 139 0.4× 121 0.5× 45 0.2× 363 1.7× 130 1.3k

Countries citing papers authored by Jun Feng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Feng

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

All Works

20 of 20 papers shown
1.
2.
Feng, Jun, et al.. (2025). A survey of Few-Shot Relation Extraction combining meta-learning with prompt learning. Neurocomputing. 647. 130534–130534.
3.
Sun, Xia, et al.. (2024). Context-enhanced framework for medical image report generation using multimodal contexts. Knowledge-Based Systems. 310. 112913–112913. 6 indexed citations
4.
Feng, Jun, et al.. (2024). Interpretable spatial-temporal attention convolutional network for rainfall forecasting. Computers & Geosciences. 185. 105535–105535. 4 indexed citations
5.
Li, Hongzhao, et al.. (2024). Prompt-Guided Generation of Structured Chest X-Ray Report Using a Pre-trained LLM. 1–6. 4 indexed citations
6.
Feng, Jun, et al.. (2023). Data-driven and knowledge-guided denoising diffusion model for flood forecasting. Expert Systems with Applications. 244. 122908–122908. 17 indexed citations
7.
Feng, Jun, et al.. (2023). Data-Driven and Knowledge-Guided Heterogeneous Graphs and Temporal Convolution Networks for Flood Forecasting. Applied Sciences. 13(12). 7191–7191. 4 indexed citations
8.
Lu, Jiamin, et al.. (2021). Efficient Subgraph Pruning & Embedding for Multi-Relation QA over Knowledge Graph. 1–8. 3 indexed citations
9.
Feng, Jun, et al.. (2020). Design of Optimal Illumination Patterns in Single-Pixel Imaging Using Image Dictionaries. IEEE photonics journal. 12(4). 1–9. 8 indexed citations
10.
Zhu, Yuelong, et al.. (2020). Flood Prediction Using Rainfall-Flow Pattern in Data-Sparse Watersheds. IEEE Access. 8. 39713–39724. 13 indexed citations
11.
Feng, Jun, et al.. (2020). Time Series Segmentation of Flood Flow Based on Bi-LG-LSTM Neural Network. 54. 162–169. 1 indexed citations
12.
Feng, Jun, et al.. (2019). Causal Analysis of Learning Performance Based on Bayesian Network and Mutual Information. Entropy. 21(11). 1102–1102. 6 indexed citations
13.
Zhu, Yuelong, et al.. (2019). A Novel Hierarchical Topic Model for Horizontal Topic Expansion With Observed Label Information. IEEE Access. 7. 184242–184253. 2 indexed citations
14.
Feng, Jun, et al.. (2018). Automatic Approach of Sentiment Lexicon Generation for Mobile Shopping Reviews. Wireless Communications and Mobile Computing. 2018(1). 17 indexed citations
15.
Wu, Yirui, et al.. (2018). Context-Aware Attention LSTM Network for Flood Prediction. 1301–1306. 30 indexed citations
16.
Feng, Jun, Minlie Huang, Yang Yang, & Xiaoyan Zhu. (2016). GAKE: Graph Aware Knowledge Embedding. International Conference on Computational Linguistics. 641–651. 41 indexed citations
17.
Li, Shijin, et al.. (2016). A new algorithm for water information extraction from high resolution remote sensing imagery. 4359–4363. 5 indexed citations
18.
Feng, Jun, Ningning Jia, Zhaohui Qi, & Xiaofen Zhang. (2015). Identification of function modules in protein-protein interaction networks by modularity optimization method. 47–51. 1 indexed citations
19.
Feng, Jun. (2012). Research on hydrological time series motifs mining.
20.
Feng, Jun, et al.. (2005). Study on an approach of feature selection for similar handwritten Chinese characters recognition. 14. 380–383. 3 indexed citations

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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