Chee Lap Chow
- Artificial Intelligence top 1%
- Neural Networks and Applications 2
- Bioengineering top 2%
- Analytical Chemistry and Sensors 4
- Signal Processing top 2%
- Statistics and Probability top 2%
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- Gas Sensing Nanomaterials and Sensors 9
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- ZnO doping and properties 4
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- Advanced Frequency and Time Standards 3
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- Ionosphere and magnetosphere dynamics 2
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- Transition Metal Oxide Nanomaterials 2
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- GNSS positioning and interference 2
- Co-authors
- C. LiuOoi Kiang TanMan Siu TseNicola MarzariNing PengQing ZhangHui HuangTimothy J. White
- Journals
- IEEE Transactions on Information Theory (3 papers)Sensors and Actuators B Chemical (2 papers)Small (2 papers)
- Partner nations
- SingaporeUnited StatesJapan
In The Last Decade
Chee Lap Chow
22 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Artificial Intelligence 1.4k
- Bioengineering 211
- Signal Processing 260
- Statistics and Probability 199
- Computer Vision and Pattern Recognition 365
Countries citing papers authored by Chee Lap Chow
This map shows the geographic impact of Chee Lap Chow'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 Chee Lap Chow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chee Lap Chow more than expected).
Fields of papers citing papers by Chee Lap Chow
This network shows the impact of papers produced by Chee Lap Chow. 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 Chee Lap Chow. The network helps show where Chee Lap Chow may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chee Lap Chow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2023 | 0 | |
| 3 | 2022 | 1 | |
| 4 | 2019 | 1 | |
| 5 | 2017 | 2 | |
| 6 | 2017 | 6 | |
| 7 | 2014 | 31 | |
| 8 | 2013 | 13 | |
| 9 | 2012 | 12 | |
| 10 | 2012 | 13 | |
| 11 | 2011 | 218 | |
| 12 | 2011 | 54 | |
| 13 | 2011 | 3 | |
| 14 | 2009 | 205 | |
| 15 | 2008 | 3 | |
| 16 | Investigations on Statistics of Terrain Height. | 1985 | 2 |
| 17 | 1976 | 1 | |
| 18 | 1973 | 30 | |
| 19 | 1970 | 470 | |
| 20 | Approximating discrete probability distributions with dependence treesbreakdown → | 1968 | 1543 |
About Chee Lap Chow
Chee Lap Chow is a scholar working on Bioengineering, Statistics, Probability and Uncertainty, Aerospace Engineering, Electrical and Electronic Engineering and Materials Chemistry, having authored 24 papers that have together received 2.7k indexed citations. Recurring topics across this work include Gas Sensing Nanomaterials and Sensors (9 papers), ZnO doping and properties (4 papers), Analytical Chemistry and Sensors (4 papers), Advanced Frequency and Time Standards (3 papers), Ionosphere and magnetosphere dynamics (2 papers), Transition Metal Oxide Nanomaterials (2 papers), Neural Networks and Applications (2 papers) and GNSS positioning and interference (2 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Bioengineering (211 citations), Signal Processing (260 citations), Statistics and Probability (199 citations) and Computer Vision and Pattern Recognition (365 citations). Chee Lap Chow has collaborated with scholars based in Singapore, United States and Japan. Frequent co-authors include C. Liu, Ooi Kiang Tan, Man Siu Tse, Nicola Marzari, Ning Peng, Qing Zhang, Hui Huang, Timothy J. White, Jun Guo and Hao Gong. Their work appears in journals such as IEEE Transactions on Information Theory, Sensors and Actuators B Chemical, Small, Acta Astronautica and Colloids and Surfaces A Physicochemical and Engineering Aspects.
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.