Kunjin Chen

2.4k total citations · 1 hit paper
19 papers, 1.8k citations indexed

About

Kunjin Chen is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Kunjin Chen has authored 19 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Electrical and Electronic Engineering, 7 papers in Control and Systems Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Kunjin Chen's work include Energy Load and Power Forecasting (7 papers), Power Systems Fault Detection (6 papers) and Smart Grid Energy Management (4 papers). Kunjin Chen is often cited by papers focused on Energy Load and Power Forecasting (7 papers), Power Systems Fault Detection (6 papers) and Smart Grid Energy Management (4 papers). Kunjin Chen collaborates with scholars based in China, United States and Switzerland. Kunjin Chen's co-authors include Jun Hu, Jinliang He, Jinliang He, Qin Wang, Kunlong Chen, Ziyu He, Yu Zhang, Zhanqing Yu, Jun Hu and Shan X. Wang and has published in prestigious journals such as IEEE Transactions on Power Systems, IEEE Journal on Selected Areas in Communications and Energy.

In The Last Decade

Kunjin Chen

19 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

Short-Term Load Forecasting With Deep Residual Networks

2018 491 citations Kunjin Chen, Kunlong Chen et al. IEEE Transactions on Smart Grid profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kunjin Chen China	16	1.5k	764	288	223	187	19	1.8k
Tianyao Ji China	29	1.9k 1.3×	1.0k 1.4×	224 0.8×	304 1.4×	74 0.4×	171	2.4k
Wenlong Liao China	20	1.2k 0.8×	401 0.5×	436 1.5×	126 0.6×	109 0.6×	82	1.8k
Shyh‐Jier Huang Taiwan	30	2.8k 1.9×	1.4k 1.9×	356 1.2×	217 1.0×	92 0.5×	133	3.3k
José L. Rueda Netherlands	26	2.2k 1.5×	1.3k 1.7×	279 1.0×	375 1.7×	68 0.4×	212	2.8k
M. Ghofrani United States	20	1.7k 1.1×	695 0.9×	365 1.3×	159 0.7×	146 0.8×	62	2.1k
Arash Moradzadeh Iran	22	899 0.6×	395 0.5×	245 0.9×	95 0.4×	241 1.3×	44	1.3k
Haidar Samet Iran	28	2.2k 1.4×	1.4k 1.9×	344 1.2×	233 1.0×	50 0.3×	152	2.9k
Ademir Nied Brazil	26	972 0.7×	360 0.5×	239 0.8×	66 0.3×	66 0.4×	86	1.6k
Linfei Yin China	25	1.2k 0.8×	684 0.9×	244 0.8×	51 0.2×	77 0.4×	135	1.8k
Dongbo Zhao United States	24	3.2k 2.1×	1.9k 2.5×	153 0.5×	338 1.5×	130 0.7×	93	3.7k

Countries citing papers authored by Kunjin Chen

Since Specialization

Citations

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

Fields of papers citing papers by Kunjin Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunjin Chen

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

All Works

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19 of 19 papers shown

Chen, Kunjin, et al.. (2023). An Explainable and Robust Method for Fault Classification and Location on Transmission Lines. IEEE Transactions on Industrial Informatics. 19(10). 10182–10191. 26 indexed citations

Zhang, Xuemin, et al.. (2020). M2GSNet: Multi-Modal Multi-Task Graph Spatiotemporal Network for Ultra-Short-Term Wind Farm Cluster Power Prediction. Applied Sciences. 10(21). 7915–7915. 35 indexed citations

Chen, Kunjin, Jun Hu, Yu Zhang, Zhanqing Yu, & Jinliang He. (2019). Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks. IEEE Journal on Selected Areas in Communications. 38(1). 119–131. 216 indexed citations

Chen, Kunjin, et al.. (2019). Scale- and Context-Aware Convolutional Non-Intrusive Load Monitoring. IEEE Transactions on Power Systems. 35(3). 2362–2373. 111 indexed citations

Duan, Lian, Jun Hu, Gen Zhao, et al.. (2019). Method of inter‐turn fault detection for next‐generation smart transformers based on deep learning algorithm. High Voltage. 4(4). 282–291. 36 indexed citations

Hu, Jun, et al.. (2019). Identification of Partial Discharge Defects Based on Deep Learning Method. IEEE Transactions on Power Delivery. 34(4). 1557–1568. 71 indexed citations

Chen, Kunjin, Kunlong Chen, Qin Wang, et al.. (2018). Short-Term Load Forecasting With Deep Residual Networks. IEEE Transactions on Smart Grid. 10(4). 3943–3952. 491 indexed citations breakdown →

Chen, Kunjin, Qin Wang, Ziyu He, et al.. (2018). Convolutional sequence to sequence non‐intrusive load monitoring. The Journal of Engineering. 2018(17). 1860–1864. 77 indexed citations

Chen, Kunjin, et al.. (2018). Learning-based data analytics: Moving towards transparent power grids. CSEE Journal of Power and Energy Systems. 4(1). 67–82. 35 indexed citations

10.

Chen, Kunlong, et al.. (2018). A novel data-driven approach for residential electricity consumption prediction based on ensemble learning. Energy. 150. 49–60. 51 indexed citations

11.

Chen, Kunlong, et al.. (2017). Practical failure recognition model of lithium-ion batteries based on partial charging process. Energy. 138. 1199–1208. 23 indexed citations

12.

Chen, Kunjin, Jun Hu, & Jinliang He. (2017). Detection and classification of transmission line faults based on unsupervised feature learning and convolutional sparse autoencoder. 1–1. 68 indexed citations

13.

Chen, Kunjin, Ziyu He, Kunlong Chen, Jun Hu, & Jinliang He. (2017). Solar energy forecasting with numerical weather predictions on a grid and convolutional networks. 1–5. 11 indexed citations

14.

Chen, Kunjin, et al.. (2017). Data-driven residential customer aggregation based on seasonal behavioral patterns. 1–5. 5 indexed citations

15.

Chen, Kunjin, Jun Hu, & Jinliang He. (2016). Detection and Classification of Transmission Line Faults Based on Unsupervised Feature Learning and Convolutional Sparse Autoencoder. IEEE Transactions on Smart Grid. 1–1. 136 indexed citations

16.

Chen, Kunjin, Jun Hu, & Jinliang He. (2016). A Framework for Automatically Extracting Overvoltage Features Based on Sparse Autoencoder. IEEE Transactions on Smart Grid. 9(2). 594–604. 79 indexed citations

17.

Chen, Kunjin, et al.. (2016). Fault detection, classification and location for transmission lines and distribution systems: a review on the methods. High Voltage. 1(1). 25–33. 274 indexed citations

18.

Chen, Kunjin, et al.. (2016). An Inversion Method for Evaluating Lightning Current Waveform Based on Time Series Neural Network. IEEE Transactions on Electromagnetic Compatibility. 59(3). 887–893. 14 indexed citations

19.

Chen, Kunjin, et al.. (2016). Probabilistic short-term wind power forecasting based on deep neural networks. 1–8. 51 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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