Pak Chung Wong
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Statistical and Nonlinear Physics top 2%
- Information Systems top 5%
- Co-authors
- R. Daniel BergeronJ. Joshua ThomasH.P. FooteKwong‐Kwok WongHong ZhouWeiwei CuiXiaoming LiHuamin Qu
- Topics
- Data Visualization and Analytics (45 papers)Complex Network Analysis Techniques (17 papers)Data Management and Algorithms (10 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignSignal Processing
- Journals
- Communications of the ACMIEEE Transactions on Power SystemsIEEE Transactions on Visualization and Computer Graphics
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Pak Chung Wong
78 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 125
- Computer Vision and Pattern Recognition 1.1k
- Artificial Intelligence 511
- Signal Processing 400
- Statistical and Nonlinear Physics 264
- Information Systems 224
Countries citing papers authored by Pak Chung Wong
This map shows the geographic impact of Pak Chung Wong'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 Pak Chung Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pak Chung Wong more than expected).
Fields of papers citing papers by Pak Chung Wong
This network shows the impact of papers produced by Pak Chung Wong. 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 Pak Chung Wong. The network helps show where Pak Chung Wong may publish in the future.
Co-authorship network of co-authors of Pak Chung Wong
This figure shows the co-authorship network connecting the top 25 collaborators of Pak Chung Wong. A scholar is included among the top collaborators of Pak Chung Wong 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 Pak Chung Wong. Pak Chung Wong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 14 | |
| 3 | Visualization and Data Analysis 2011 | 1 |
| 4 | 2 | |
| 5 | 14 | |
| 6 | Visualization and Data Analysis 2010 | 1 |
| 7 | 10 | |
| 8 | Managing Complex Network Operation with Predictive Analytics | 11 |
| 9 | 61 | |
| 10 | 193 | |
| 11 | 7 | |
| 12 | 30 | |
| 13 | 34 | |
| 14 | 135 | |
| 15 | IEEE Symposium on Information Visualization 2001 : INFOVIS 2001, 22-23 October, 2001, San Diego, California, USA | 3 |
| 16 | 7 | |
| 17 | 23 | |
| 18 | 31 | |
| 19 | 48 | |
| 20 | 12 |
About Pak Chung Wong
Pak Chung Wong is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Statistical and Nonlinear Physics, having authored 79 papers that have together received 1.8k indexed citations. Recurring topics across this work include Data Visualization and Analytics (45 papers), Complex Network Analysis Techniques (17 papers) and Data Management and Algorithms (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Computer Graphics and Computer-Aided Design (146 citations) and Signal Processing (400 citations). Pak Chung Wong has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include R. Daniel Bergeron, J. Joshua Thomas, H.P. Foote, Kwong‐Kwok Wong, Hong Zhou, Weiwei Cui, Xiaoming Li, Huamin Qu, Han‐Wei Shen and Paul Whitney. Their work appears in journals such as Communications of the ACM, IEEE Transactions on Power Systems and IEEE Transactions on Visualization and Computer Graphics.
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.