Han Hai

931 citations
69 papers · 644 · h-index 12

Impact in

Papers in

Han Hai

60 papers receiving 627 citations

Peers

Han Hai
Comparison fields: 5 of 85
  • Acoustics and Ultrasonics 9
  • Electrical and Electronic Engineering 417
  • Computer Networks and Communications 151
  • Computer Vision and Pattern Recognition 97
  • Artificial Intelligence 114
Replace Zhefu Wu with:
Zhefu Wu China
Wenbo Xu China
Victor B. Lawrence United States
Neeraj Varshney India
S. J. Thiruvengadam India
Teng Zhang United States
Han Hai relative to Zhefu Wu China Zhefu Wu's profile →
Citations per field
00.5×1.5×2.3×
Zhefu Wu · 1×
Citations per year

Countries citing papers authored by Han Hai

Since Specialization
Citations

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

Fields of papers citing papers by Han Hai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Han Hai, 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 Han Hai Line = papers co-authored together Han Hai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201993
2 201976
3 201771
4 201761
5 201937
6 201337
7 201727
8 201918
9 201717
10 201915
11 202113
12 202512
13 202011
14 202111
15 201811
16 20199
17 20098
18 20237
19 20207
20 20187

About Han Hai

Han Hai is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Aerospace Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 69 papers that have together received 644 indexed citations. Recurring topics across this work include Advanced Wireless Communication Technologies (30 papers), Cooperative Communication and Network Coding (11 papers), Optical Wireless Communication Technologies (10 papers), Advanced MIMO Systems Optimization (9 papers), Satellite Communication Systems (8 papers), Error Correcting Code Techniques (6 papers), Energy Harvesting in Wireless Networks (6 papers) and PAPR reduction in OFDM (6 papers). The work is most often cited by research in Acoustics and Ultrasonics (9 citations), Electrical and Electronic Engineering (417 citations), Computer Networks and Communications (151 citations), Computer Vision and Pattern Recognition (97 citations) and Artificial Intelligence (114 citations). Han Hai has collaborated with scholars based in China, South Korea and Macao. Frequent co-authors include Xueqin Jiang, Jun Li, Miaowen Wen, Yuyang Peng, Shuping Dang, Dajiang Lu, Wei Duan, Meihua Liao, Wenqi He and Xiang Peng. Their work appears in journals such as IEEE Communications Letters, IEEE Transactions on Vehicular Technology, IEEE Wireless Communications Letters, Physical Communication and IEEE Access.

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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