Ming‐Hung Shih
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Information Systems top 10%
- Blockchain Technology Applications and Security
- User Authentication and Security Systems
Papers in
-
- Blockchain Technology Applications and Security 6
-
- Cryptography and Data Security 3
- Data Stream Mining Techniques 3
- Co-authors
- Dong‐Her Shih (28 shared papers)Hsiu‐Sen Chiang (5 shared papers)Binshan Lin (2 shared papers)Cheng-Fu Yu (1 shared paper)C.P. Chang (1 shared paper)P.W. Kao (1 shared paper)David C. Yen (7 shared papers)Trong Duc Nguyen (2 shared papers)
- Journals
- IEEE Access (2 papers)Journal of Clinical Medicine (2 papers)Expert Systems with Applications (2 papers)Multimedia Tools and Applications (1 paper)Applied Sciences (1 paper)
- Partner nations
- United StatesTaiwanJapan
In The Last Decade
Ming‐Hung Shih
30 papers receiving 344 citations
Peers
Comparison fields: 5 of 102
- Signal Processing 65
- Information Systems 104
- Transportation 18
- Computer Networks and Communications 62
- Artificial Intelligence 74
Countries citing papers authored by Ming‐Hung Shih
This map shows the geographic impact of Ming‐Hung Shih'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‐Hung Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Hung Shih more than expected).
Fields of papers citing papers by Ming‐Hung Shih
This network shows the impact of papers produced by Ming‐Hung Shih. 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‐Hung Shih. The network helps show where Ming‐Hung Shih may publish in the future.
Co-authors
The 19 scholars most cited alongside Ming‐Hung Shih, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 67 | |
| 2 | 2020 | 57 | |
| 3 | 2008 | 56 | |
| 4 | 2022 | 25 | |
| 5 | 2014 | 24 | |
| 6 | 2021 | 17 | |
| 7 | 2022 | 15 | |
| 8 | 2015 | 15 | |
| 9 | 2015 | 15 | |
| 10 | 2011 | 14 | |
| 11 | 2022 | 12 | |
| 12 | 2019 | 10 | |
| 13 | 2011 | 7 | |
| 14 | 2024 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2021 | 3 | |
| 20 | 2017 | 3 |
About Ming‐Hung Shih
Ming‐Hung Shih is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Cardiology and Cardiovascular Medicine, having authored 33 papers that have together received 371 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (6 papers), Data Management and Algorithms (4 papers), Cryptography and Data Security (3 papers), COVID-19 epidemiological studies (3 papers), EEG and Brain-Computer Interfaces (3 papers), Data Stream Mining Techniques (3 papers), ECG Monitoring and Analysis (3 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Signal Processing (65 citations), Information Systems (104 citations), Transportation (18 citations), Computer Networks and Communications (62 citations) and Artificial Intelligence (74 citations). Ming‐Hung Shih has collaborated with scholars based in United States, Taiwan and Japan. Frequent co-authors include Dong‐Her Shih, Hsiu‐Sen Chiang, Binshan Lin, Cheng-Fu Yu, C.P. Chang, P.W. Kao, David C. Yen, Trong Duc Nguyen, Bojian Xu and Divesh Srivastava. Their work appears in journals such as IEEE Access, Journal of Clinical Medicine, Expert Systems with Applications, Multimedia Tools and Applications and Applied Sciences.
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.