Yuang Jiang

744 total citations · 1 hit paper
15 papers, 365 citations indexed

About

Yuang Jiang is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Yuang Jiang has authored 15 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Networks and Communications, 7 papers in Artificial Intelligence and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Yuang Jiang's work include Software-Defined Networks and 5G (6 papers), Network Traffic and Congestion Control (4 papers) and Topic Modeling (3 papers). Yuang Jiang is often cited by papers focused on Software-Defined Networks and 5G (6 papers), Network Traffic and Congestion Control (4 papers) and Topic Modeling (3 papers). Yuang Jiang collaborates with scholars based in United States, China and Singapore. Yuang Jiang's co-authors include Leandros Tassiulas, Kin K. Leung, Wei‐Han Lee, Bong Jun Ko, Shiqiang Wang, Víctor Valls, T. V. Lakshman, Sarit Mukherjee, Murali Kodialam and Irene Li and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, BMJ Open and Nuclear Engineering and Design.

In The Last Decade

Yuang Jiang

13 papers receiving 360 citations

Hit Papers

Model Pruning Enables Efficient Federated Learning on Edg... 2022 2026 2023 2024 2022 50 100 150 200 250

Peers

Yuang Jiang
Comparison fields: 5 of 58
  • Artificial Intelligence 238
  • Computer Networks and Communications 111
  • Electrical and Electronic Engineering 67
  • Information Systems 45
  • Computer Vision and Pattern Recognition 42
Replace Renping Liu with:
Renping Liu China
Víctor Valls Ireland
Zhe Qu China
Moming Duan China
Bimal Ghimire United States
Zengxiang Li China
Xuanli He Australia
Sagnik Sarkar India
Renping Liu China View profile →
Citations per field, relative to Yuang Jiang
Yuang Jiang · 1×
Citations per year, relative to Yuang Jiang
Yuang Jiang · 1×

Countries citing papers authored by Yuang Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Yuang Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuang Jiang

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

All Works

15 of 15 papers shown
# Work Indexed citations
1 3
2 0
3 5
4 3
5 0
6
Model Pruning Enables Efficient Federated Learning on Edge Devices breakdown →
288
7 13
8 10
9 8
10
Fast Reinforcement Learning Algorithms for Resource Allocation in Data Centers
2
11 5
12 1
13 14
14 1
15 12

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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