Ming Jin

27 papers and 525 indexed citations i.

About

Ming Jin is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research. According to data from OpenAlex, Ming Jin has authored 27 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Signal Processing and 5 papers in Management Science and Operations Research. Recurrent topics in Ming Jin’s work include Time Series Analysis and Forecasting (8 papers), Anomaly Detection Techniques and Applications (6 papers) and Stock Market Forecasting Methods (5 papers). Ming Jin is often cited by papers focused on Time Series Analysis and Forecasting (8 papers), Anomaly Detection Techniques and Applications (6 papers) and Stock Market Forecasting Methods (5 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, Feng Xia, Yixin Liu, Chuan Zhou, Lianhua Chi, Qingsong Wen, Yi‐Ping Phoebe Chen and Khoa T. Phan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Co-authorship network of co-authors of Ming Jin i

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.

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).

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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