Chase Q. Wu

2.2k total citations · 1 hit paper
149 papers, 1.5k citations indexed

About

Chase Q. Wu is a scholar working on Computer Networks and Communications, Information Systems and Electrical and Electronic Engineering. According to data from OpenAlex, Chase Q. Wu has authored 149 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 109 papers in Computer Networks and Communications, 51 papers in Information Systems and 32 papers in Electrical and Electronic Engineering. Recurrent topics in Chase Q. Wu's work include Cloud Computing and Resource Management (42 papers), Distributed and Parallel Computing Systems (34 papers) and Software-Defined Networks and 5G (27 papers). Chase Q. Wu is often cited by papers focused on Cloud Computing and Resource Management (42 papers), Distributed and Parallel Computing Systems (34 papers) and Software-Defined Networks and 5G (27 papers). Chase Q. Wu collaborates with scholars based in United States, China and Australia. Chase Q. Wu's co-authors include Hongpo Zhang, Lulu Huang, Zhanbo Li, Xiangyu Lin, Aiqin Hou, Michelle Zhu, Liang Bao, Nageswara S. V. Rao, Tong Shu and Dantong Yu and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Access and Sensors.

In The Last Decade

Chase Q. Wu

136 papers receiving 1.5k citations

Hit Papers

An effective convolutional neural network based on SMOTE ... 2020 2026 2022 2024 2020 50 100 150 200

Peers

Chase Q. Wu
Comparison fields: 5 of 101
  • Computer Networks and Communications 1.0k
  • Information Systems 542
  • Artificial Intelligence 441
  • Electrical and Electronic Engineering 268
  • Signal Processing 192
Replace Devesh Tiwari with:
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Haiyang Wang China
Vincent Omollo Nyangaresi Kenya
Xiaofeng Meng China
Chris Karlof United States
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Agostino Forestiero Italy
Xiao Yu China
Devesh Tiwari United States View profile →
Citations per field, relative to Chase Q. Wu
Chase Q. Wu · 1×
Citations per year, relative to Chase Q. Wu
Chase Q. Wu · 1×

Countries citing papers authored by Chase Q. Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chase Q. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chase Q. 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 Chase Q. Wu. The network helps show where Chase Q. Wu may publish in the future.

Co-authorship network of co-authors of Chase Q. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chase Q. Wu. A scholar is included among the top collaborators of Chase Q. 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 Chase Q. Wu. Chase Q. 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 0
2 15
3 1
4 17
5 0
6 1
7 3
8 2
9 2
10 3
11 0
12 4
13 4
14 0
15 20
16 2
17
Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning
2
18 7
19
Performance analysis of Wald-statistic based network detection methods for radiation sources
5
20 10

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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