Hongda Wu

907 citations
30 papers · 632 · 1 hit paper · h-index 10

Impact in

Papers in

Hongda Wu

28 papers receiving 621 citations

Hongda Wu's Hit Papers

Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data 2022 · 128 citations
1280+1+2Years since publication4080120

Peers

Hongda Wu
Comparison fields: 5 of 104
  • Computer Science Applications 54
  • Artificial Intelligence 283
  • Health, Toxicology and Mutagenesis 117
  • Pollution 73
  • Computer Networks and Communications 87
Replace Miao Jiang with:
Miao Jiang China
Zhiyu Hao China
Mostafa Ezziyyani Morocco
Waheed Anwar Pakistan
Yi‐Jing Liu China
Xinyu Huang China
Olivier Pereira Belgium
Hongda Wu relative to Miao Jiang China Miao Jiang's profile →
Citations per field
00.5×3.3×
Miao Jiang · 1×
Citations per year

Countries citing papers authored by Hongda Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hongda Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hongda Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hongda Wu Line = papers co-authored together Hongda Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021139
2
Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data
Hit paper breakdown →
2022128
3 201374
4 201246
5 201441
6 201536
7 201832
8 201826
9 202326
10 202218
11 20138
12 20218
13 20186
14 20146
15 20195
16 20224
17 20174
18 20244
19 20203
20 20173

About Hongda Wu

Hongda Wu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Networks and Communications, Health, Toxicology and Mutagenesis and Signal Processing, having authored 30 papers that have together received 632 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (6 papers), Environmental Toxicology and Ecotoxicology (5 papers), Mobile Crowdsensing and Crowdsourcing (5 papers), Antenna Design and Optimization (4 papers), Advanced MIMO Systems Optimization (3 papers), Pesticide Exposure and Toxicity (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Blind Source Separation Techniques (2 papers). The work is most often cited by research in Computer Science Applications (54 citations), Artificial Intelligence (283 citations), Health, Toxicology and Mutagenesis (117 citations), Pollution (73 citations) and Computer Networks and Communications (87 citations). Hongda Wu has collaborated with scholars based in China, Canada and United Kingdom. Frequent co-authors include Ping Wang, Houjuan Xing, Shiwen Xu, Libiao Jin, Qiyou Xu, Yan Jiang, Xu Wang, Ziwei Zhang, Pu Zhang and Shu Li. Their work appears in journals such as EURASIP Journal on Wireless Communications and Networking, IEEE Transactions on Vehicular Technology, IEEE Transactions on Network Science and Engineering, IEEE Wireless Communications and Environmental Toxicology and Pharmacology.

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.

Explore authors with similar magnitude of impact