Jun-Wei Lin

679 citations
30 papers · 486 · h-index 11

Impact in

Papers in

Jun-Wei Lin

27 papers receiving 475 citations

Peers

Jun-Wei Lin
Comparison fields: 5 of 90
  • Software 175
  • Human Factors and Ergonomics 36
  • Signal Processing 74
  • Information Systems 148
  • Insect Science 57
Replace Josef Pichler with:
Josef Pichler Austria
Guangwei Li China
Gregory T. Sullivan Türkiye
John Brant United States
Heather J. Goldsby United States
Nic Herndon United States
Chris Tofts United Kingdom
David Heise United States
Roberto Tedesco Brazil
Marcelo Serrano Zanetti Switzerland
Jun-Wei Lin relative to Josef Pichler Austria Josef Pichler's profile →
Citations per field
00.5×8.9×
Josef Pichler · 1×
Citations per year

Countries citing papers authored by Jun-Wei Lin

Since Specialization
Citations

This map shows the geographic impact of Jun-Wei Lin'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 Lin 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 Lin more than expected).

Fields of papers citing papers by Jun-Wei Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014122
2 200964
3 201953
4 202138
5 201932
6 202030
7 200924
8 202024
9 202213
10 201713
11 201812
12 20229
13 20228
14 20227
15 20246
16 20135
17 20224
18 20084
19 20074
20 20233

About Jun-Wei Lin

Jun-Wei Lin is a scholar working on Software, Computer Networks and Communications, Information Systems, Signal Processing and Electrical and Electronic Engineering, having authored 30 papers that have together received 486 indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (10 papers), Advanced Malware Detection Techniques (6 papers), Software System Performance and Reliability (5 papers), Software Engineering Research (3 papers), Vector-borne infectious diseases (2 papers), Lymphoma Diagnosis and Treatment (2 papers), Chronic Lymphocytic Leukemia Research (2 papers) and Prenatal Screening and Diagnostics (2 papers). The work is most often cited by research in Software (175 citations), Human Factors and Ergonomics (36 citations), Signal Processing (74 citations), Information Systems (148 citations) and Insect Science (57 citations). Jun-Wei Lin has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Sam Malek, Chin‐Yu Huang, Reyhaneh Jabbarvand, Kevin J. Hackett, Chien‐Yueh Lee, Christopher Childers, Monica F. Poelchau, Gary Moore, Han Lin and Jay D. Evans. Their work appears in journals such as Prenatal Diagnosis, Parasitology Research, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, British Journal of Haematology and Frontiers in Oncology.

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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