Ming Jin

2.2k citations
37 papers · 991 · 3 hit papers · h-index 11

Impact in

    • Advanced Graph Neural Networks
    • Anomaly Detection Techniques and Applications
    • Neural Networks and Applications
    • Time Series Analysis and Forecasting

Papers in

Ming Jin

31 papers receiving 980 citations

Ming Jin's Hit Papers

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects 2024 · 100 citations
1000+1+2Years since publication100200300

Peers

Ming Jin
Comparison fields: 5 of 93
  • Artificial Intelligence 596
  • Signal Processing 194
  • Statistical and Nonlinear Physics 122
  • Computer Networks and Communications 156
  • Computer Vision and Pattern Recognition 136
Replace Zhisong Pan with:
Zhisong Pan China
Jieren Cheng China
Athanasios Kehagias Greece
Xu Zhou China
Xiao Ling China
Tong Zhao China
Ruoyu Li China
Weiqing Liu China
Malay K. Pakhira India
Yuan Yang China
Ming Jin relative to Zhisong Pan China Zhisong Pan's profile →
Citations per field
00.5×3.8×
Zhisong Pan · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Ming 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 Ming Jin Line = papers co-authored together Ming Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Graph Self-Supervised Learning: A Survey
Hit paper breakdown →
2022353
2
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
Hit paper breakdown →
2024177
3 2022106
4
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
Hit paper breakdown →
2024100
5 202176
6 202353
7 202216
8 201915
9 202213
10 201912
11 201111
12 202410
13 20245
14 20254
15 20194
16 20154
17 20254
18
Reliability Testing for Blind Processing Results of LFM Signals Based on NP Criterion
20133
19 20253
20
An adaptive bilateral filtering method for image processing
20043

About Ming Jin

Ming Jin is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Information Systems and Management Science and Operations Research, having authored 37 papers that have together received 991 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (6 papers), Stock Market Forecasting Methods (4 papers), Advanced Graph Neural Networks (4 papers), Traffic Prediction and Management Techniques (3 papers), Network Security and Intrusion Detection (3 papers), Data Stream Mining Techniques (3 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Artificial Intelligence (596 citations), Signal Processing (194 citations), Statistical and Nonlinear Physics (122 citations), Computer Networks and Communications (156 citations) and Computer Vision and Pattern Recognition (136 citations). Ming Jin has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Shirui Pan, Yu Zheng, Philip S. Yu, Yixin Liu, Chuan Zhou, Yuan-Fang Li, Qingsong Wen, Huan Yee Koh, Daniele Zambon and Cesare Alippi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems and Nature Communications.

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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