Armin Ai

909 citations
21 papers · 723 · h-index 11

Impact in

    • Electrospun Nanofibers in Biomedical Applications
    • Silk-based biomaterials and applications
    • Wound Healing and Treatments

Papers in

    • Electrospun Nanofibers in Biomedical Applications 9
    • Tissue Engineering and Regenerative Medicine 7

Armin Ai

21 papers receiving 711 citations

Peers

Armin Ai
Comparison fields: 5 of 87
  • Biomaterials 402
  • Rehabilitation 145
  • Developmental Neuroscience 42
  • Genetics 84
  • Cellular and Molecular Neuroscience 138
Replace Sangho Roh with:
Sangho Roh South Korea
Zhongyang Liu China
Arman Ai Iran
Elham Hasanzadeh Iran
Yingji Mao China
Mohammad Ali Derakhshan Iran
Alan Hibbitts Ireland
Emıne Alarçın Türkiye
Jiah Shin Chin Singapore
Armin Ai relative to Sangho Roh South Korea Sangho Roh's profile →
Citations per field
00.5×1.5×2.4×
Sangho Roh · 1×
Citations per year

Countries citing papers authored by Armin Ai

Since Specialization
Citations

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

Fields of papers citing papers by Armin Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020212
2 2019128
3 201381
4 201453
5 201347
6 201345
7 201834
8 201918
9 201915
10 201613
11 201613
12 20189
13 20209
14 20208
15 20208
16 20148
17 20136
18 20245
19 20225
20 20145

About Armin Ai

Armin Ai is a scholar working on Biomaterials, Surgery, Biomedical Engineering, Cellular and Molecular Neuroscience and Molecular Biology, having authored 21 papers that have together received 723 indexed citations. Recurring topics across this work include Electrospun Nanofibers in Biomedical Applications (9 papers), Bone Tissue Engineering Materials (8 papers), Tissue Engineering and Regenerative Medicine (7 papers), Nerve injury and regeneration (5 papers), Mesenchymal stem cell research (2 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Research on Leishmaniasis Studies (2 papers) and Wound Healing and Treatments (2 papers). The work is most often cited by research in Biomaterials (402 citations), Rehabilitation (145 citations), Developmental Neuroscience (42 citations), Genetics (84 citations) and Cellular and Molecular Neuroscience (138 citations). Armin Ai has collaborated with scholars based in Iran, United States and Canada. Frequent co-authors include Jafar Ai, Somayeh Ebrahimi‐Barough, Arash Goodarzi, Majid Salehi, Shiva Asadpour, Arian Ehterami, Lida Moradi, Saeed Farzamfar, Saeid Kargozar and Hamed Nosrati. Their work appears in journals such as International Journal of Polymeric Materials, Journal of Biomedical Materials Research Part A, Scientific Reports, Materials Science and Engineering C and International Journal of Biological Macromolecules.

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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