Janet Wang
Impact in
- Health Informatics top 5%
Papers in ⓘ
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- Low-power high-performance VLSI design 9
- Advanced Memory and Neural Computing 6
- VLSI and FPGA Design Techniques 6
- Semiconductor materials and devices 5
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- Signaling Pathways in Disease 2
- Co-authors
- V. Wee Yong (4 shared papers)Manoj K. Mishra (3 shared papers)Cláudia Silva (3 shared papers)Sarma Vrudhula (1 shared paper)Shane Hollmer (4 shared papers)J. J. Sáenz (4 shared papers)Foroozan Koushan (4 shared papers)John R. Jameson (3 shared papers)
- Journals
- Applied Physics Letters (2 papers)Nature Communications (2 papers)Blood (1 paper)IEEE Electron Device Letters (1 paper)Genes Chromosomes and Cancer (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Janet Wang
38 papers receiving 698 citations
Peers
Comparison fields: 5 of 111
- Health Informatics 33
- Research and Theory 11
- Hardware and Architecture 75
- Neurology 67
- Biological Psychiatry 16
Countries citing papers authored by Janet Wang
This map shows the geographic impact of Janet Wang'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 Janet Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janet Wang more than expected).
Fields of papers citing papers by Janet Wang
This network shows the impact of papers produced by Janet Wang. 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 Janet Wang. The network helps show where Janet Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Janet Wang, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 78 | |
| 2 | 2012 | 74 | |
| 3 | 2022 | 70 | |
| 4 | 2012 | 63 | |
| 5 | 2004 | 60 | |
| 6 | 2011 | 42 | |
| 7 | 2022 | 39 | |
| 8 | 2012 | 37 | |
| 9 | 2022 | 28 | |
| 10 | 1991 | 27 | |
| 11 | 2009 | 20 | |
| 12 | 2021 | 19 | |
| 13 | 2012 | 19 | |
| 14 | 2013 | 18 | |
| 15 | 2010 | 17 | |
| 16 | 2009 | 14 | |
| 17 | 2022 | 12 | |
| 18 | 2009 | 11 | |
| 19 | 2019 | 10 | |
| 20 | 2007 | 10 |
About Janet Wang
Janet Wang is a scholar working on Electrical and Electronic Engineering, Molecular Biology, Hardware and Architecture, Computer Networks and Communications and Genetics, having authored 39 papers that have together received 721 indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (9 papers), Advanced Memory and Neural Computing (6 papers), VLSI and FPGA Design Techniques (6 papers), VLSI and Analog Circuit Testing (5 papers), Semiconductor materials and devices (5 papers), Interconnection Networks and Systems (4 papers), Signaling Pathways in Disease (2 papers) and Galectins and Cancer Biology (2 papers). The work is most often cited by research in Health Informatics (33 citations), Research and Theory (11 citations), Hardware and Architecture (75 citations), Neurology (67 citations) and Biological Psychiatry (16 citations). Janet Wang has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include V. Wee Yong, Manoj K. Mishra, Cláudia Silva, Sarma Vrudhula, Shane Hollmer, J. J. Sáenz, Foroozan Koushan, John R. Jameson, Michael N. Kozicki and Ahmed Louri. Their work appears in journals such as Applied Physics Letters, Nature Communications, Blood, IEEE Electron Device Letters and Genes Chromosomes and Cancer.
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.