S. Wee
Impact in
- Transplantation top 2%
- Renal Transplantation Outcomes and Treatments
- Signal Processing top 5%
- Video Coding and Compression Technologies
Papers in
- Immunology 14
- T-cell and B-cell Immunology 8
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- Advanced Data Compression Techniques 8
- Co-authors
- J Apostolopoulos (13 shared papers)Wai-Tian Tan (5 shared papers)Tina Wong (1 shared paper)A. Benedict Cosimi (15 shared papers)Alejandro Aruffo (2 shared papers)Tatsuo Kawai (8 shared papers)Robert B. Colvin (8 shared papers)Gary L. Schieven (2 shared papers)
- Journals
- Transplantation (12 papers)IEEE Transactions on Multimedia (3 papers)Human Immunology (3 papers)The Journal of Experimental Medicine (2 papers)Biotechnology Advances (1 paper)
- Partner nations
- United StatesFranceSwitzerland
In The Last Decade
S. Wee
44 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 82
- Transplantation 172
- Signal Processing 210
- Immunology 378
- Computer Vision and Pattern Recognition 328
- Computer Networks and Communications 362
Countries citing papers authored by S. Wee
This map shows the geographic impact of S. Wee'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 S. Wee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Wee more than expected).
Fields of papers citing papers by S. Wee
This network shows the impact of papers produced by S. Wee. 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 S. Wee. The network helps show where S. Wee may publish in the future.
Co-authors
The 25 scholars most cited alongside S. Wee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 224 | |
| 2 | 2004 | 164 | |
| 3 | 1995 | 127 | |
| 4 | 1993 | 77 | |
| 5 | 2005 | 55 | |
| 6 | 1993 | 54 | |
| 7 | 2004 | 43 | |
| 8 | 1996 | 42 | |
| 9 | 2006 | 38 | |
| 10 | 2005 | 36 | |
| 11 | 2001 | 33 | |
| 12 | 1999 | 30 | |
| 13 | 2001 | 29 | |
| 14 | 2007 | 27 | |
| 15 | 2006 | 26 | |
| 16 | 1998 | 25 | |
| 17 | 1995 | 25 | |
| 18 | 1989 | 24 | |
| 19 | 1995 | 24 | |
| 20 | 2003 | 23 |
About S. Wee
S. Wee is a scholar working on Immunology, Computer Vision and Pattern Recognition, Computer Networks and Communications, Transplantation and Surgery, having authored 45 papers that have together received 1.4k indexed citations. Recurring topics across this work include Renal Transplantation Outcomes and Treatments (8 papers), T-cell and B-cell Immunology (8 papers), Advanced Data Compression Techniques (8 papers), Video Coding and Compression Technologies (7 papers), Peer-to-Peer Network Technologies (7 papers), Caching and Content Delivery (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and Advanced Data Storage Technologies (5 papers). The work is most often cited by research in Transplantation (172 citations), Signal Processing (210 citations), Immunology (378 citations), Computer Vision and Pattern Recognition (328 citations) and Computer Networks and Communications (362 citations). S. Wee has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include J Apostolopoulos, Wai-Tian Tan, Tina Wong, A. Benedict Cosimi, Alejandro Aruffo, Tatsuo Kawai, Robert B. Colvin, Gary L. Schieven, Songqing Chen and Bo Shen. Their work appears in journals such as Transplantation, IEEE Transactions on Multimedia, Human Immunology, The Journal of Experimental Medicine and Biotechnology Advances.
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.