Cheong-Fat Chan
- Signal Processing top 5%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Chiu‐Sing ChoyKong‐Pang PunWai-Kuen ChamJ.E. FrancaN. H. CheungChun‐Pong YuHao MinWei Han
- Topics
- Analog and Mixed-Signal Circuit Design (21 papers)Radio Frequency Integrated Circuit Design (13 papers)Low-power high-performance VLSI design (12 papers)
In The Last Decade
Cheong-Fat Chan
40 papers receiving 333 citations
Peers
Comparison fields: 5 of 58
- Signal Processing 149
- Electrical and Electronic Engineering 134
- Artificial Intelligence 111
- Biomedical Engineering 79
- Computer Vision and Pattern Recognition 77
Countries citing papers authored by Cheong-Fat Chan
This map shows the geographic impact of Cheong-Fat Chan'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 Cheong-Fat Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheong-Fat Chan more than expected).
Fields of papers citing papers by Cheong-Fat Chan
This network shows the impact of papers produced by Cheong-Fat Chan. 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 Cheong-Fat Chan. The network helps show where Cheong-Fat Chan may publish in the future.
Co-authorship network of co-authors of Cheong-Fat Chan
This figure shows the co-authorship network connecting the top 25 collaborators of Cheong-Fat Chan. A scholar is included among the top collaborators of Cheong-Fat Chan 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 Cheong-Fat Chan. Cheong-Fat Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | 198 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 6 | |
| 17 | 1 | |
| 18 | Pipelined Dataflow Architecture of a Small Processor. | 1 |
| 19 | 12 | |
| 20 | An Asynchronous Cell Library for Self-Timed System Designs (Special Issue on Asynchronous Circuit and System Design) | 8 |
About Cheong-Fat Chan
Cheong-Fat Chan is a scholar working on Hardware and Architecture, Signal Processing and Electrical and Electronic Engineering, having authored 46 papers that have together received 369 indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (21 papers), Radio Frequency Integrated Circuit Design (13 papers) and Low-power high-performance VLSI design (12 papers). The work is most often cited by research in Signal Processing (149 citations), Hardware and Architecture (35 citations) and Computer Vision and Pattern Recognition (77 citations). Cheong-Fat Chan has collaborated with scholars based in Hong Kong, China and Portugal. Frequent co-authors include Chiu‐Sing Choy, Kong‐Pang Pun, Wai-Kuen Cham, J.E. Franca, N. H. Cheung, Chun‐Pong Yu, Hao Min, Wei Han, Ka Nang Leung and Tan Lee. Their work appears in journals such as Journal of Applied Physics, IEEE Journal of Solid-State Circuits and IEEE Transactions on Circuits and Systems for Video Technology.
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.