Ming-Chuan Wu
- Computer Networks and Communications top 5%
- Information Systems top 2%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Nicolas BrunoAlejandro BuchmannSrikanth KandulaJingren ZhouSameer AgarwalIon StoicaPer-Åke LarsonRonnie Chaiken
- Topics
- Advanced Database Systems and Queries (9 papers)Cloud Computing and Resource Management (5 papers)Data Management and Algorithms (5 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Ming-Chuan Wu
24 papers receiving 526 citations
Peers
Comparison fields: 5 of 63
- Computer Networks and Communications 378
- Information Systems 318
- Signal Processing 158
- Artificial Intelligence 143
- Computer Vision and Pattern Recognition 97
Countries citing papers authored by Ming-Chuan Wu
This map shows the geographic impact of Ming-Chuan Wu'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-Chuan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming-Chuan Wu more than expected).
Fields of papers citing papers by Ming-Chuan Wu
This network shows the impact of papers produced by Ming-Chuan Wu. 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-Chuan Wu. The network helps show where Ming-Chuan Wu may publish in the future.
Co-authorship network of co-authors of Ming-Chuan Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Chuan Wu. A scholar is included among the top collaborators of Ming-Chuan Wu 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 Ming-Chuan Wu. Ming-Chuan Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 12 | |
| 3 | 17 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | 15 | |
| 7 | 23 | |
| 8 | 32 | |
| 9 | 2 | |
| 10 | Re-optimizing data-parallel computing | 129 |
| 11 | 106 | |
| 12 | 3 | |
| 13 | 22 | |
| 14 | 7 | |
| 15 | 7 | |
| 16 | 6 | |
| 17 | 75 | |
| 18 | Encoded Bitmap Indexes and Their Use for Data Warehouse Optimization | 3 |
| 19 | 18 | |
| 20 | 37 |
About Ming-Chuan Wu
Ming-Chuan Wu is a scholar working on Chemical Health and Safety, Computer Networks and Communications and Hardware and Architecture, having authored 24 papers that have together received 562 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (9 papers), Cloud Computing and Resource Management (5 papers) and Data Management and Algorithms (5 papers). The work is most often cited by research in Computer Networks and Communications (378 citations), Signal Processing (158 citations) and Information Systems (318 citations). Ming-Chuan Wu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Nicolas Bruno, Alejandro Buchmann, Srikanth Kandula, Jingren Zhou, Sameer Agarwal, Ion Stoica, Per-Åke Larson, Jingren Zhou, Ronnie Chaiken and YongChul Kwon. Their work appears in journals such as Optics Letters, Proceedings of the VLDB Endowment and Journal of Consumer Marketing.
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.