Da Kuang
- Computational Mathematics top 5%
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- Complex Network Analysis Techniques 4
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- Face and Expression Recognition 3
- Artificial Intelligence top 5%
- Text and Document Classification Technologies 3
- Sentiment Analysis and Opinion Mining 2
- Media Technology top 5%
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- Genomics and Rare Diseases 4
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- Genomics and Phylogenetic Studies 3
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- SARS-CoV-2 and COVID-19 Research 2
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- Misinformation and Its Impacts 2
- Cited by
- Computational MathematicsStatistical and Nonlinear PhysicsComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterología (2 papers)Bioinformatics (3 papers)Journal of Molecular Biology (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Da Kuang
23 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Computational Mathematics 29
- Statistical and Nonlinear Physics 157
- Computer Vision and Pattern Recognition 226
- Artificial Intelligence 277
- Media Technology 74
Countries citing papers authored by Da Kuang
This map shows the geographic impact of Da Kuang'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 Da Kuang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Kuang more than expected).
Fields of papers citing papers by Da Kuang
This network shows the impact of papers produced by Da Kuang. 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 Da Kuang. The network helps show where Da Kuang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Da Kuang, 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 | 2024 | 12 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2022 | 0 | |
| 5 | 2021 | 16 | |
| 6 | 2020 | 31 | |
| 7 | 2020 | 8 | |
| 8 | 2018 | 5 | |
| 9 | The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactionsbreakdown → | 2018 | 314 |
| 10 | 2018 | 15 | |
| 11 | 2017 | 11 | |
| 12 | 2017 | 24 | |
| 13 | 2016 | 37 | |
| 14 | Toward Social Media Opinion Mining for Sustainability Research | 2015 | 4 |
| 15 | 2015 | 1 | |
| 16 | 2013 | 50 | |
| 17 | 2012 | 290 | |
| 18 | A New Web Search Engine with Learning Hierarchy | 2012 | 0 |
| 19 | 2011 | 6 | |
| 20 | 2005 | 4 |
About Da Kuang
Da Kuang is a scholar working on Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 25 papers that have together received 1.0k indexed citations. Recurring topics across this work include Genomics and Rare Diseases (4 papers), Complex Network Analysis Techniques (4 papers), Genomics and Phylogenetic Studies (3 papers), Face and Expression Recognition (3 papers), Text and Document Classification Technologies (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Sentiment Analysis and Opinion Mining (2 papers) and Misinformation and Its Impacts (2 papers). The work is most often cited by research in Computational Mathematics (29 citations), Statistical and Nonlinear Physics (157 citations) and Computer Vision and Pattern Recognition (226 citations). Da Kuang has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Haesun Park, Chris Ding, Sangwoon Yun, Mayank Choudhary, Ross C. Hardison, Ting Wang, Jie Xu, Fan Song, Daofeng Li and Lijun Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and Journal of Molecular Biology.
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.