May Win Naing

3.4k citations
42 papers · 2.7k · h-index 24

Impact in

Papers in

    • 3D Printing in Biomedical Research 25
    • Bone Tissue Engineering Materials 5
    • Innovative Microfluidic and Catalytic Techniques Innovation 5
    • Additive Manufacturing and 3D Printing Technologies 12

May Win Naing

41 papers receiving 2.6k citations

Peers

May Win Naing
Comparison fields: 5 of 129
  • Automotive Engineering 1.1k
  • Biomaterials 589
  • Biomedical Engineering 1.9k
  • Rehabilitation 230
  • Molecular Medicine 59
Replace Zongjie Wang with:
Zongjie Wang Canada
Hyeongjin Lee South Korea
Hyungseok Lee South Korea
Wei Long Ng Singapore
Young‐Joon Seol South Korea
Madhuri Dey United States
Ji Seung Lee South Korea
Sylvain Catros France
Xuanyi Ma United States
Liesbeth Tytgat Belgium
May Win Naing relative to Zongjie Wang Canada Zongjie Wang's profile →
Citations per field
00.5×2.6×
Zongjie Wang · 1×
Citations per year

Countries citing papers authored by May Win Naing

Since Specialization
Citations

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

Fields of papers citing papers by May Win Naing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by May Win Naing. 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 May Win Naing. The network helps show where May Win Naing may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016220
2 2019219
3 2018212
4 2018199
5 2016199
6 2017184
7 2018136
8 2005117
9 2005109
10 202099
11 201794
12 201885
13 201782
14 201982
15 201681
16 202079
17 202073
18 201355
19 202047
20 201845

About May Win Naing

May Win Naing is a scholar working on Biomedical Engineering, Automotive Engineering, Molecular Biology, Biomaterials and Rehabilitation, having authored 42 papers that have together received 2.7k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (25 papers), Additive Manufacturing and 3D Printing Technologies (12 papers), Wound Healing and Treatments (5 papers), Bone Tissue Engineering Materials (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (5 papers), Viral Infectious Diseases and Gene Expression in Insects (4 papers), Tissue Engineering and Regenerative Medicine (4 papers) and Silk-based biomaterials and applications (3 papers). The work is most often cited by research in Automotive Engineering (1.1k citations), Biomaterials (589 citations), Biomedical Engineering (1.9k citations), Rehabilitation (230 citations) and Molecular Medicine (59 citations). May Win Naing has collaborated with scholars based in Singapore, United Kingdom and Russia. Frequent co-authors include Wai Yee Yeong, Wei Long Ng, Deepak Choudhury, Han W. Tun, Tianyi Wang, Satnam Singh, Chee Kai Chua, Kah Fai Leong, Shuai Wang and Jia Min Lee. Their work appears in journals such as Cytotherapy, Scientific Reports, Trends in biotechnology, International Journal of Bioprinting and Biomaterials Science.

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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