Yu-Ming Chang
- Computer Networks and Communications top 5%
- Hardware and Architecture top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Molecular Biology
- Co-authors
- Yuan-Hao ChangTei‐Wei KuoHsiang-Pang LiChun‐Nan HsuYu-Shi LinCheng-Ju KuoI‐Fang ChungMing-Chang Yang
- Topics
- Advanced Data Storage Technologies (31 papers)Parallel Computing and Optimization Techniques (20 papers)Caching and Content Delivery (18 papers)
- Cited by
- Hardware and ArchitectureComputer Networks and CommunicationsComputational Theory and Mathematics
- Partner nations
- TaiwanHong KongUnited States
In The Last Decade
Yu-Ming Chang
48 papers receiving 583 citations
Peers
Comparison fields: 5 of 58
- Computer Networks and Communications 320
- Hardware and Architecture 167
- Artificial Intelligence 132
- Electrical and Electronic Engineering 113
- Molecular Biology 93
Countries citing papers authored by Yu-Ming Chang
This map shows the geographic impact of Yu-Ming Chang'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 Yu-Ming Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Ming Chang more than expected).
Fields of papers citing papers by Yu-Ming Chang
This network shows the impact of papers produced by Yu-Ming Chang. 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 Yu-Ming Chang. The network helps show where Yu-Ming Chang may publish in the future.
Co-authorship network of co-authors of Yu-Ming Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Ming Chang. A scholar is included among the top collaborators of Yu-Ming Chang 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 Yu-Ming Chang. Yu-Ming Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 31 | |
| 4 | 3 | |
| 5 | 9 | |
| 6 | 16 | |
| 7 | 2 | |
| 8 | 8 | |
| 9 | 2 | |
| 10 | 8 | |
| 11 | 23 | |
| 12 | 17 | |
| 13 | 22 | |
| 14 | Periodic Step Size Adaptation for Single Pass On-line Learning | 1 |
| 15 | 6 | |
| 16 | 2 | |
| 17 | 6 | |
| 18 | Rich Feature Set, Unification of Bidirectional Parsing and Dictionary Filtering for High F-Score Gene Mention Tagging. | 28 |
| 19 | Enhancing Automatic Chinese Essay Scoring System from Figures-of-Speech | 7 |
| 20 | 56 |
About Yu-Ming Chang
Yu-Ming Chang is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computational Theory and Mathematics, having authored 49 papers that have together received 596 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (31 papers), Parallel Computing and Optimization Techniques (20 papers) and Caching and Content Delivery (18 papers). The work is most often cited by research in Hardware and Architecture (167 citations), Computer Networks and Communications (320 citations) and Computational Theory and Mathematics (70 citations). Yu-Ming Chang has collaborated with scholars based in Taiwan, Hong Kong and United States. Frequent co-authors include Yuan-Hao Chang, Tei‐Wei Kuo, Hsiang-Pang Li, Chun‐Nan Hsu, Yu-Shi Lin, Cheng-Ju Kuo, I‐Fang Chung, Ming-Chang Yang, Pi-Cheng Hsiu and Po‐Chun Huang. Their work appears in journals such as Bioinformatics, IEEE Transactions on Computers and Machine Learning.
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.