Carole-Jean Wu

5.7k total citations
78 papers, 2.0k citations indexed

About

Carole-Jean Wu is a scholar working on Computer Networks and Communications, Hardware and Architecture and Electrical and Electronic Engineering. According to data from OpenAlex, Carole-Jean Wu has authored 78 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Networks and Communications, 37 papers in Hardware and Architecture and 37 papers in Electrical and Electronic Engineering. Recurrent topics in Carole-Jean Wu's work include Parallel Computing and Optimization Techniques (36 papers), Advanced Data Storage Technologies (23 papers) and Green IT and Sustainability (18 papers). Carole-Jean Wu is often cited by papers focused on Parallel Computing and Optimization Techniques (36 papers), Advanced Data Storage Technologies (23 papers) and Green IT and Sustainability (18 papers). Carole-Jean Wu collaborates with scholars based in United States, Israel and South Korea. Carole-Jean Wu's co-authors include Shin-Ying Lee, Margaret Martonosi, Young Geun Kim, Akhil Arunkumar, Aamer Jaleel, Udit Gupta, Gu-Yeon Wei, Simon C. Steely, Joel Emer and David Brooks and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Internet of Things Journal and IEEE Transactions on Mobile Computing.

In The Last Decade

Carole-Jean Wu

73 papers receiving 1.9k citations

Peers

Carole-Jean Wu
Comparison fields: 5 of 82
  • Computer Networks and Communications 1.2k
  • Hardware and Architecture 933
  • Electrical and Electronic Engineering 697
  • Information Systems 499
  • Artificial Intelligence 408
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Citations per field, relative to Carole-Jean Wu
Carole-Jean Wu · 1×
Citations per year, relative to Carole-Jean Wu
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Countries citing papers authored by Carole-Jean Wu

Since Specialization
Citations

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

Fields of papers citing papers by Carole-Jean Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carole-Jean Wu. 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 Carole-Jean Wu. The network helps show where Carole-Jean Wu may publish in the future.

Co-authorship network of co-authors of Carole-Jean Wu

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 7
3 2
4 0
5 0
6 7
7 12
8 0
9 11
10 2
11 7
12 3
13 5
14 8
15
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
6
16 105
17 15
18 11
19 55
20 11

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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