Hang Chen

484 citations
26 papers · 346 · h-index 10

Impact in

Papers in

Hang Chen

24 papers receiving 339 citations

Peers

Hang Chen
Comparison fields: 5 of 79
  • Molecular Medicine 54
  • Biomaterials 51
  • Polymers and Plastics 51
  • Surfaces, Coatings and Films 18
  • Acoustics and Ultrasonics 2
Replace David Mérida with:
David Mérida Spain
Tejas Shah United States
Jinnan Zhang China
John Fonner United States
Hyunwoo Choi South Korea
Zilu Zhang China
Kai Nan China
Xinjiang Chen China
Pieter Wuytens Belgium
Hang Chen relative to David Mérida Spain David Mérida's profile →
Citations per field
00.5×1.7×
David Mérida · 1×
Citations per year

Countries citing papers authored by Hang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202266
2 201956
3 201944
4 202041
5 200525
6 201717
7 201616
8 201414
9 201612
10 20239
11 20239
12 20227
13 20217
14 20243
15 20113
16 20153
17 20223
18 20152
19
[Mitochondrial signal peptide guides EGFP-GRP75 fusion proteins into mitochondria].
20162
20 20042

About Hang Chen

Hang Chen is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering and Molecular Biology, having authored 26 papers that have together received 346 indexed citations. Recurring topics across this work include Cryptography and Data Security (6 papers), Cloud Data Security Solutions (6 papers), Wireless Communication Networks Research (4 papers), Advanced Wireless Network Optimization (4 papers), Security and Verification in Computing (3 papers), Polymer Surface Interaction Studies (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Advanced Sensor and Energy Harvesting Materials (2 papers). The work is most often cited by research in Molecular Medicine (54 citations), Biomaterials (51 citations), Polymers and Plastics (51 citations), Surfaces, Coatings and Films (18 citations) and Acoustics and Ultrasonics (2 citations). Hang Chen has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Di Xiang, Pingchuan Sun, Yue Xu, Guolin Wu, Feifan Li, Dharma P. Agrawal, Wei Li, Chunfu Jia, Yanming Wang and Lihua Lin. Their work appears in journals such as Oncotarget, IEEE Transactions on Cloud Computing, Polymer Chemistry, Information Sciences and IEEE Transactions on Mobile Computing.

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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