Sky Faber

448 citations
7 papers · 121 indexed · h-index 5
Topics
Cryptography and Data Security (5 papers)Privacy-Preserving Technologies in Data (5 papers)Single-cell and spatial transcriptomics (1 paper)
Journals
ComputerNeural NetworkseScholarship (California Digital Library)
Partner nations
United StatesCanada

In The Last Decade

Sky Faber

6 papers receiving 116 citations

Peers

Sky Faber
Comparison fields: 5 of 33
  • Artificial Intelligence 84
  • Molecular Biology 31
  • Cancer Research 21
  • Public Health, Environmental and Occupational Health 20
  • Genetics 15
Replace Teruyoshi Hishiki with:
Teruyoshi Hishiki Japan
Hong-Woo Chun South Korea
Knox Carey United States
Hansheng Xue China
Sucheendra K. Palaniappan Japan
Yonghwa Choi South Korea
Vida Ravanmehr United States
André Lamúrias Portugal
Benjamin Hescott United States
Nataliya Sklyar United Kingdom
Sky Faber relative to Teruyoshi Hishiki Japan Teruyoshi Hishiki's profile →
Citations per field
00.5×
Teruyoshi Hishiki · 1×
Citations per year

Countries citing papers authored by Sky Faber

Since Specialization
Citations

This map shows the geographic impact of Sky Faber'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 Sky Faber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sky Faber more than expected).

Fields of papers citing papers by Sky Faber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sky Faber. 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 Sky Faber. The network helps show where Sky Faber may publish in the future.

Co-authorship network of co-authors of Sky Faber

This figure shows the co-authorship network connecting the top 25 collaborators of Sky Faber. A scholar is included among the top collaborators of Sky Faber 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 Sky Faber. Sky Faber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 2
2
Variants of Privacy Preserving Set Intersection and their Practical Applications
0
3 5
4 42
5
GenoDroid: Are Privacy-Preserving Genomic Tests Ready for Prime Time?
4
6 41
7 27

About Sky Faber

Sky Faber is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology, having authored 7 papers that have together received 121 indexed citations. Recurring topics across this work include Cryptography and Data Security (5 papers), Privacy-Preserving Technologies in Data (5 papers) and Single-cell and spatial transcriptomics (1 paper). The work is most often cited by research in Artificial Intelligence (84 citations), Cancer Research (21 citations) and Biophysics (5 citations). Sky Faber has collaborated with scholars based in United States and Canada. Frequent co-authors include Gene Tsudik, Emiliano De Cristofaro, Paolo Gasti, Karim El Defrawy, Lydia Ng, Chris Lau, Susan M. Sunkin, Mike Hawrylycz, Ed S. Lein and Vance Faber. Their work appears in journals such as Computer, Neural Networks and eScholarship (California Digital Library).

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.

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