Ming Jin

2.0k total citations · 3 hit papers
35 papers, 864 citations indexed

About

Ming Jin is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Ming Jin has authored 35 papers receiving a total of 864 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 14 papers in Signal Processing and 5 papers in Computer Networks and Communications. Recurrent topics in Ming Jin's work include Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Graph Neural Networks (4 papers). Ming Jin is often cited by papers focused on Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Graph Neural Networks (4 papers). Ming Jin collaborates with scholars based in Australia, China and United States. Ming Jin's co-authors include Shirui Pan, Yu Zheng, Philip S. Yu, Yixin Liu, Chuan Zhou, Feng Xia, Yuan-Fang Li, Qingsong Wen, Huan Yee Koh and Lianhua Chi and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Ming Jin

28 papers receiving 847 citations

Hit Papers

Graph Self-Supervised Learning: A Survey 2022 2026 2023 2024 2022 2024 2024 100 200 300
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. Graph Self-Supervised Learning: A Survey
    2022 330 citations Ming Jin, Shirui Pan et al. IEEE Transactions on Knowledge and Data Engineering profile →
  2. A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
    2024 139 citations Ming Jin, Huan Yee Koh et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
  3. Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
    2024 83 citations Kexin Zhang, Qingsong Wen et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Jin Australia 11 537 168 141 125 117 35 864
Noseong Park South Korea 17 525 1.0× 186 1.1× 307 2.2× 174 1.4× 288 2.5× 84 1.1k
Jieren Cheng China 18 485 0.9× 145 0.9× 257 1.8× 352 2.8× 193 1.6× 84 998
Xu Zhou China 16 245 0.5× 204 1.2× 340 2.4× 130 1.0× 183 1.6× 72 880
Qingquan Song United States 11 567 1.1× 56 0.3× 56 0.4× 239 1.9× 120 1.0× 23 1.0k
Tong Zhao China 16 512 1.0× 67 0.4× 183 1.3× 122 1.0× 141 1.2× 97 956
Ruoyu Li China 11 441 0.8× 61 0.4× 127 0.9× 221 1.8× 94 0.8× 31 810
Junyang Chen China 16 423 0.8× 42 0.3× 90 0.6× 290 2.3× 181 1.5× 74 900
Ye Yuan China 16 429 0.8× 55 0.3× 94 0.7× 290 2.3× 247 2.1× 52 1.0k
Malay K. Pakhira India 7 569 1.1× 151 0.9× 57 0.4× 264 2.1× 120 1.0× 22 915

Countries citing papers authored by Ming Jin

Since Specialization
Citations

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

Fields of papers citing papers by Ming Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Jin. A scholar is included among the top collaborators of Ming 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 Ming Jin. Ming Jin 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.
Li, Zhao, Linhao Luo, Ming Jin, et al.. (2025). Large lithium-ion battery model for secure shared electric bike battery in smart cities. Nature Communications. 16(1). 8415–8415. 1 indexed citations
2.
Xue, Hao, Ming Jin, Shirui Pan, & Flora D. Salim. (2025). Transforming Urban Dynamics: Harnessing Large Language Models for Smarter Mobility. IEEE Intelligent Systems. 40(2). 5–7. 4 indexed citations
3.
Liang, Yuxuan, Haomin Wen, Ming Jin, et al.. (2025). Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey. 6063–6073. 4 indexed citations
4.
Jin, Ming, Yuan-Fang Li, Tian Zhou, et al.. (2025). Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(6). 4926–4939.
5.
Jin, Ming, Yufei Tang, Laurent M. Chérubin, et al.. (2025). OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories. 5822–5830.
6.
Yang, Yiyuan, Ming Jin, Haomin Wen, et al.. (2025). A Survey on Diffusion Models for Time Series and Spatio-Temporal Data. ACM Computing Surveys. 58(8). 1–39. 1 indexed citations
7.
Zhang, Daokun, et al.. (2024). Towards complex dynamic physics system simulation with graph neural ordinary equations. Neural Networks. 176. 106341–106341. 8 indexed citations
8.
Jin, Ming, Huan Yee Koh, Qingsong Wen, et al.. (2024). A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 10466–10485. 139 indexed citations breakdown →
9.
Zhang, Kexin, Qingsong Wen, Chaoli Zhang, et al.. (2024). Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(10). 6775–6794. 83 indexed citations breakdown →
10.
Zheng, Yu, Huan Yee Koh, Ming Jin, et al.. (2023). Correlation-Aware Spatial–Temporal Graph Learning for Multivariate Time-Series Anomaly Detection. IEEE Transactions on Neural Networks and Learning Systems. 35(9). 11802–11816. 44 indexed citations
11.
Jin, Ming, et al.. (2023). Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7405–7413.
12.
Zheng, Yizhen, Ming Jin, Shirui Pan, et al.. (2022). Toward Graph Self-Supervised Learning With Contrastive Adjusted Zooming. IEEE Transactions on Neural Networks and Learning Systems. 35(7). 8882–8896. 13 indexed citations
13.
Jin, Ming, Yu Zheng, Yuan-Fang Li, et al.. (2022). Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs. IEEE Transactions on Knowledge and Data Engineering. 35(9). 9168–9180. 93 indexed citations
14.
Xiong, Xi, et al.. (2019). A Clickthrough Rate Prediction Algorithm Based on Users’ Behaviors. IEEE Access. 7. 174782–174792. 4 indexed citations
15.
Liu, Shigang, et al.. (2019). Optimized Coefficient Vector and Sparse Representation-Based Classification Method for Face Recognition. IEEE Access. 8. 8668–8674. 14 indexed citations
16.
Jin, Ming, et al.. (2018). EFFECTS OF LAUNCHING PARAMETERS ON THE SEPARATION TRAJECTORY OF INTERNAL WEAPONS. 工程力学. 35(1). 246–256. 1 indexed citations
17.
Jin, Ming, et al.. (2015). Backscattering measurements of plasma coated target in high-enthalpy wind tunnel. Acta Physica Sinica. 64(20). 205205–205205. 4 indexed citations
18.
Jin, Ming. (2013). Reliability Testing for Blind Processing Results of LFM Signals Based on NP Criterion. Dianzi xuebao. 3 indexed citations
19.
Jin, Ming, et al.. (2007). Velocity Measurement among Correlation Sonar by Hybrid Particle Swarm Optimization Algorithm.. International MultiConference of Engineers and Computer Scientists. 195–197. 1 indexed citations
20.
Jin, Ming. (2004). An adaptive bilateral filtering method for image processing. Guangdian gongcheng. 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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