Justin Chen

30 papers receiving 597 citations

Peers

Justin Chen
Comparison fields: 5 of 117
  • Biomaterials 186
  • Surfaces, Coatings and Films 25
  • Biomedical Engineering 153
  • Materials Chemistry 142
  • Molecular Medicine 14
Replace Marcus Bäck with:
Marcus Bäck Sweden
Miguel Lino Portugal
Laurence Burroughs United Kingdom
Jasmin Matuszak Germany
Naixin Liu China
Yuefei Zhu United States
Robert Hennig Germany
Ju Eun Kim South Korea
Kathrin Abstiens Germany
Grazia M. L. Messina Italy
Justin Chen relative to Marcus Bäck Sweden Marcus Bäck's profile →
Citations per field
00.5×3.5×
Marcus Bäck · 1×
Citations per year

Countries citing papers authored by Justin Chen

Since Specialization
Citations

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

Fields of papers citing papers by Justin Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011333
2 201259
3 200850
4 201020
5 201118
6 202115
7 202313
8 201911
9 202011
10 202310
11 20118
12 20237
13 20237
14 20226
15 20245
16 20214
17 20224
18 20223
19 20233
20 20193

About Justin Chen

Justin Chen is a scholar working on Surgery, Computer Vision and Pattern Recognition, Algebra and Number Theory, Artificial Intelligence and Computational Theory and Mathematics, having authored 35 papers that have together received 607 indexed citations. Recurring topics across this work include Polynomial and algebraic computation (4 papers), Commutative Algebra and Its Applications (3 papers), Multimodal Machine Learning Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Rings, Modules, and Algebras (2 papers), Topic Modeling (2 papers), Algebraic Geometry and Number Theory (2 papers) and Electrochemical Analysis and Applications (2 papers). The work is most often cited by research in Biomaterials (186 citations), Surfaces, Coatings and Films (25 citations), Biomedical Engineering (153 citations), Materials Chemistry (142 citations) and Molecular Medicine (14 citations). Justin Chen has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include Z. Hong Zhou, Xiang Wang, Jeffrey I. Zink, Zongxi Li, Huan Meng, Connie Huang, André E. Nel, Tian Xia, Haiyuan Zhang and Sijie Lin. Their work appears in journals such as Clinical Anatomy, IEEE Transactions on Visualization and Computer Graphics, Journal of Virology, Drug Metabolism and Disposition and Artificial Intelligence in Medicine.

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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