Johnson Kin
Impact in
- Hardware and Architecture top 2%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
- Network Packet Processing and Optimization
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- Interconnection Networks and Systems
- Advanced Data Storage Technologies
- Caching and Content Delivery
Papers in
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- Parallel Computing and Optimization Techniques 10
- Embedded Systems Design Techniques 9
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- Advanced Data Storage Technologies 3
- Distributed and Parallel Computing Systems 2
- Interconnection Networks and Systems 2
- Co-authors
- William H. Mangione-Smith (9 shared papers)Munish Kumar Gupta (2 shared papers)Darko Kirovski (3 shared papers)Miodrag Potkonjak (4 shared papers)Chunho Lee (4 shared papers)
- Journals
- IEEE Transactions on Computers (1 paper)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)International Journal of Parallel Programming (1 paper)International Symposium on Microarchitecture (1 paper)
- Partner nations
- United States
In The Last Decade
Johnson Kin
9 papers receiving 320 citations
Peers
Comparison fields: 5 of 19
- Hardware and Architecture 324
- Computer Networks and Communications 216
- Electrical and Electronic Engineering 139
- Artificial Intelligence 32
- Software 3
Countries citing papers authored by Johnson Kin
This map shows the geographic impact of Johnson Kin'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 Johnson Kin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johnson Kin more than expected).
Fields of papers citing papers by Johnson Kin
This network shows the impact of papers produced by Johnson Kin. 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 Johnson Kin. The network helps show where Johnson Kin may publish in the future.
Co-authors
The 5 scholars most cited alongside Johnson Kin, 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 | 2002 | 187 | |
| 2 | 2000 | 60 | |
| 3 | 1997 | 45 | |
| 4 | 1999 | 20 | |
| 5 | 2002 | 16 | |
| 6 | 1998 | 8 | |
| 7 | 1999 | 4 | |
| 8 | 2003 | 4 | |
| 9 | 2001 | 1 | |
| 10 | 1999 | 1 |
About Johnson Kin
Johnson Kin is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Sociology and Political Science and Artificial Intelligence, having authored 10 papers that have together received 346 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Embedded Systems Design Techniques (9 papers), Advanced Data Storage Technologies (3 papers), Low-power high-performance VLSI design (2 papers), Distributed and Parallel Computing Systems (2 papers), Interconnection Networks and Systems (2 papers), Multimedia Communication and Technology (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Hardware and Architecture (324 citations), Computer Networks and Communications (216 citations), Electrical and Electronic Engineering (139 citations), Artificial Intelligence (32 citations) and Software (3 citations). Johnson Kin has collaborated with scholars based in United States. Frequent co-authors include William H. Mangione-Smith, Munish Kumar Gupta, Darko Kirovski, Miodrag Potkonjak and Chunho Lee. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, International Journal of Parallel Programming and International Symposium on Microarchitecture.
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.