Die Hu

2.0k citations
104 papers · 1.5k · h-index 18

Impact in

Papers in

Die Hu

91 papers receiving 1.4k citations

Peers

Die Hu
Comparison fields: 5 of 137
  • Signal Processing 158
  • Electrical and Electronic Engineering 485
  • Computer Networks and Communications 199
  • Computational Mathematics 5
  • Cognitive Neuroscience 129
Replace Mark S. Leeson with:
Mark S. Leeson United Kingdom
Amr Badr Egypt
Andrew Howard United States
Cheng Xiang Singapore
Tarun Kumar Sharma India
Amitava Datta Australia
J.F. Tasič Slovenia
Ashraf A. M. Khalaf Egypt
S. Ramakrishnan United States
Yapeng Wang Macao
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Citations per field
00.5×1.5×1.9×
Mark S. Leeson · 1×
Citations per year

Countries citing papers authored by Die Hu

Since Specialization
Citations

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

Fields of papers citing papers by Die Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015132
2 202297
3 202185
4 201784
5 201983
6 201583
7 201280
8 200678
9 201369
10 200757
11 200544
12 201929
13 201829
14 201526
15 201923
16 202122
17 201820
18 202320
19 201317
20 202217

About Die Hu

Die Hu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Molecular Biology, Computer Vision and Pattern Recognition and Plant Science, having authored 104 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Wireless Communication Techniques (18 papers), Advanced MIMO Systems Optimization (15 papers), Wireless Communication Networks Research (8 papers), Cooperative Communication and Network Coding (7 papers), Full-Duplex Wireless Communications (5 papers), Plant Stress Responses and Tolerance (5 papers), Face and Expression Recognition (4 papers) and Plant Gene Expression Analysis (4 papers). The work is most often cited by research in Signal Processing (158 citations), Electrical and Electronic Engineering (485 citations), Computer Networks and Communications (199 citations), Computational Mathematics (5 citations) and Cognitive Neuroscience (129 citations). Die Hu has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include Lianghua He, Jun Wu, Xiaodong Wang, Tony Lelièvre, Ying Wen, Kai Song, Yao Tong, Xiaodong Wang, Karen M. von Deneen and MengChu Zhou. Their work appears in journals such as IEEE Wireless Communications Letters, Frontiers in Plant Science, IEEE Transactions on Wireless Communications, Photodiagnosis and Photodynamic Therapy and IEEE Transactions on Vehicular Technology.

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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