Junyang Jin

1.7k citations
17 papers · 163 · h-index 7

Impact in

Papers in

Junyang Jin

14 papers receiving 157 citations

Peers

Junyang Jin
Comparison fields: 5 of 65
  • Automotive Engineering 46
  • Safety, Risk, Reliability and Quality 27
  • Control and Systems Engineering 44
  • Statistics, Probability and Uncertainty 13
  • Statistical and Nonlinear Physics 19
Replace Luca Biggio with:
Luca Biggio Switzerland
Shane Barratt United States
Humberto Verdejo Chile
Karthikeyan Balasubramaniam United States
Farnaz Safdarian United States
Fabrizio De Italy
Y. H. Wan China
Ioannis Simaiakis United States
Juan Anzurez Marín Mexico
Junyang Jin relative to Luca Biggio Switzerland Luca Biggio's profile →
Citations per field
00.5×
Luca Biggio · 1×
Citations per year

Countries citing papers authored by Junyang Jin

Since Specialization
Citations

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

Fields of papers citing papers by Junyang Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 202162
2 202328
3 202221
4 201910
5 20208
6 20236
7 20206
8 20175
9 20195
10 20234
11 20212
12 20182
13 20202
14
An Improved Active Contour Model With Fuzzy Approach
19961
15 20151
16 20220
17 20240

About Junyang Jin

Junyang Jin is a scholar working on Control and Systems Engineering, Molecular Biology, Oncology, Artificial Intelligence and Electrical and Electronic Engineering, having authored 17 papers that have together received 163 indexed citations. Recurring topics across this work include Control Systems and Identification (4 papers), Fault Detection and Control Systems (3 papers), Statistical Methods and Inference (2 papers), Gaussian Processes and Bayesian Inference (2 papers), Energy Load and Power Forecasting (2 papers), Machine Fault Diagnosis Techniques (2 papers), Model Reduction and Neural Networks (2 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Automotive Engineering (46 citations), Safety, Risk, Reliability and Quality (27 citations), Control and Systems Engineering (44 citations), Statistics, Probability and Uncertainty (13 citations) and Statistical and Nonlinear Physics (19 citations). Junyang Jin has collaborated with scholars based in China, United Kingdom and Luxembourg. Frequent co-authors include Yong Zhang, Jianliang Chen, Yi Li, Xiujuan Zheng, Jia Ding, Yuxuan Zhao, Jorge Gonçalves, Ye Yuan, Cheng Cheng and Alex Webb. Their work appears in journals such as IEEE Transactions on Automatic Control, Nature Machine Intelligence, Applied Energy, Gynecologic Oncology and International Journal of Systems Science.

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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