Kevin Chiu
- Computational Mechanics top 10%
- Statistical and Nonlinear Physics top 10%
- Aerospace Engineering
- Information Systems top 10%
- Artificial Intelligence
- Co-authors
- Mark FugeWei ChenDarren EdgeJames A. LandayJing ZhaoRamesh RaskarNaoya KoizumiKshitij Marwah
- Topics
- Advanced Multi-Objective Optimization Algorithms (3 papers)Model Reduction and Neural Networks (3 papers)Video Surveillance and Tracking Methods (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignStatistical and Nonlinear PhysicsHuman-Computer Interaction
- Journals
- AIAA Journal2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition WorkshopsAIAA Scitech 2019 Forum
- Partner nations
- United StatesNetherlandsChina
In The Last Decade
Kevin Chiu
9 papers receiving 258 citations
Peers
Comparison fields: 5 of 54
- Computational Mechanics 66
- Statistical and Nonlinear Physics 62
- Aerospace Engineering 53
- Information Systems 49
- Artificial Intelligence 47
Countries citing papers authored by Kevin Chiu
This map shows the geographic impact of Kevin Chiu'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 Kevin Chiu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Chiu more than expected).
Fields of papers citing papers by Kevin Chiu
This network shows the impact of papers produced by Kevin Chiu. 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 Kevin Chiu. The network helps show where Kevin Chiu may publish in the future.
Co-authorship network of co-authors of Kevin Chiu
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Chiu. A scholar is included among the top collaborators of Kevin Chiu 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 Kevin Chiu. Kevin Chiu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 96 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 62 | |
| 6 | 95 | |
| 7 | 3 | |
| 8 | 10 | |
| 9 | 2 |
About Kevin Chiu
Kevin Chiu is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 271 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (3 papers), Model Reduction and Neural Networks (3 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (18 citations), Statistical and Nonlinear Physics (62 citations) and Human-Computer Interaction (26 citations). Kevin Chiu has collaborated with scholars based in United States, Netherlands and China. Frequent co-authors include Mark Fuge, Wei Chen, Darren Edge, James A. Landay, Jing Zhao, Ramesh Raskar, Naoya Koizumi, Kshitij Marwah, Tyler Hutchison and Daniel Saakes. Their work appears in journals such as AIAA Journal, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops and AIAA Scitech 2019 Forum.
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.