Jun Wei Liu

418 citations
14 papers · 321 · h-index 5

Impact in

Papers in

    • Shape Memory Alloy Transformations 3
    • Titanium Alloys Microstructure and Properties 2
    • Hydrogen Storage and Materials 2
    • Aluminum Alloys Composites Properties 2
    • Advanced materials and composites 2

Jun Wei Liu

12 papers receiving 304 citations

Peers

Jun Wei Liu
Comparison fields: 5 of 105
  • Signal Processing 44
  • Information Systems 55
  • Molecular Biology 159
  • Cancer Research 27
  • Geography, Planning and Development 9
Replace Chia-Hsin Liu with:
Chia-Hsin Liu Taiwan
Wooil Kim South Korea
André Frotta Müller Germany
Kyu‐Baek Hwang South Korea
Xiao Yu Zhang China
Chaohao Li China
Yanqi Xie China
Ayushi Verma India
Ying Tan United States
Jun Wei Liu relative to Chia-Hsin Liu Taiwan Chia-Hsin Liu's profile →
Citations per field
00.5×1.5×2.3×
Chia-Hsin Liu · 1×
Citations per year

Countries citing papers authored by Jun Wei Liu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wei Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Wei Liu. 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 Jun Wei Liu. The network helps show where Jun Wei Liu may publish in the future.

Co-authors

The 21 scholars most cited alongside Jun Wei Liu, 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 Jun Wei Liu Line = papers co-authored together Jun Wei Liu links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2002184
2 200591
3 201026
4 20164
5 20144
6 20142
7 20122
8 20112
9 20131
10 20141
11 20151
12 20121
13 20131
14 20131

About Jun Wei Liu

Jun Wei Liu is a scholar working on Materials Chemistry, Mechanical Engineering, Molecular Biology, Biomaterials and Pharmacology, having authored 14 papers that have together received 321 indexed citations. Recurring topics across this work include Shape Memory Alloy Transformations (3 papers), Magnesium Alloys: Properties and Applications (2 papers), Titanium Alloys Microstructure and Properties (2 papers), Aluminum Alloys Composites Properties (2 papers), Hydrogen Storage and Materials (2 papers), Advanced materials and composites (2 papers), Advanced biosensing and bioanalysis techniques (1 paper) and Data Management and Algorithms (1 paper). The work is most often cited by research in Signal Processing (44 citations), Information Systems (55 citations), Molecular Biology (159 citations), Cancer Research (27 citations) and Geography, Planning and Development (9 citations). Jun Wei Liu has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Dean G. Tang, Dhyan Chandra, Jeremy Mennis, Kristin Beebe, Michele D. Vos, Farida Latif, Arndt Hartmann, Luke B. Hesson, Laura Gordon and Howard Donninger. Their work appears in journals such as Molecular and Cellular Biology, Advanced materials research, Journal of Biological Chemistry, Transactions in GIS and Materials science forum.

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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