Nicholas Kong
Impact in
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- Data Visualization and Analytics
- Video Analysis and Summarization
- Handwritten Text Recognition Techniques
- Image Retrieval and Classification Techniques
- Signal Processing top 10%
- Time Series Analysis and Forecasting
Papers in
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- Wikis in Education and Collaboration 4
- Co-authors
- Maneesh AgrawalaJeffrey HeerManolis SavvaLi Fei-FeiMarti A. HearstGeorge FitzmauriceTovi GrossmanBjörn Hartmann
- Journals
- IEEE Transactions on Visualization and Computer Graphics (1 paper)UC Berkeley (1 paper)Zenodo (CERN European Organization for Nuclear Research) (1 paper)
- Partner nations
- United StatesFranceCanada
In The Last Decade
Nicholas Kong
11 papers receiving 539 citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 455
- Signal Processing 98
- Human-Computer Interaction 37
- Computer Science Applications 30
- Artificial Intelligence 176
Countries citing papers authored by Nicholas Kong
This map shows the geographic impact of Nicholas Kong'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 Nicholas Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Kong more than expected).
Fields of papers citing papers by Nicholas Kong
This network shows the impact of papers produced by Nicholas Kong. 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 Nicholas Kong. The network helps show where Nicholas Kong may publish in the future.
Co-authors
The 16 scholars most cited alongside Nicholas Kong, 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 | 2020 | 1 | |
| 2 | 2014 | 60 | |
| 3 | Techniques for Modifying and Augmenting Existing Charts for Improved Usability | 2013 | 1 |
| 4 | 2012 | 66 | |
| 5 | 2012 | 44 | |
| 6 | 2011 | 3 | |
| 7 | 2011 | 171 | |
| 8 | 2011 | 0 | |
| 9 | 2011 | 7 | |
| 10 | 2011 | 3 | |
| 11 | 2009 | 193 | |
| 12 | 2009 | 16 |
About Nicholas Kong
Nicholas Kong is a scholar working on Communication, Computer Science Applications, Computer Vision and Pattern Recognition, Information Systems and Management and Information Systems, having authored 12 papers that have together received 565 indexed citations. Recurring topics across this work include Data Visualization and Analytics (5 papers), Wikis in Education and Collaboration (4 papers), Web Data Mining and Analysis (4 papers), Software Engineering Research (2 papers), Video Analysis and Summarization (2 papers), Personal Information Management and User Behavior (1 paper), Speech and Audio Processing (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (455 citations), Signal Processing (98 citations), Human-Computer Interaction (37 citations), Computer Science Applications (30 citations) and Artificial Intelligence (176 citations). Nicholas Kong has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Maneesh Agrawala, Jeffrey Heer, Manolis Savva, Li Fei-Fei, Marti A. Hearst, George Fitzmaurice, Tovi Grossman, Björn Hartmann, Ed H. and Gregorio Convertino. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, UC Berkeley and Zenodo (CERN European Organization for Nuclear Research).
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.