Jimmy Wang

48 papers receiving 1.0k citations

Peers

Jimmy Wang
Comparison fields: 5 of 128
  • Health Informatics 29
  • Nephrology 95
  • Transplantation 29
  • Immunology 210
  • Endocrinology, Diabetes and Metabolism 129
Replace Masaya Sato with:
Masaya Sato Japan
Yongcheng He China
Aaron D. Aguirre United States
Liqiang Zhou China
Chih‐Wei Chen Taiwan
Daniël M. de Bruin Netherlands
Tokio Matsuzaki Japan
Hiroyuki Kurosawa Japan
Jon N. Marsh United States
Brian Wang United States
Jimmy Wang relative to Masaya Sato Japan Masaya Sato's profile →
Citations per field
00.5×10×20×29×
Masaya Sato · 1×
Citations per year

Countries citing papers authored by Jimmy Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jimmy Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017297
2 201681
3 201980
4 201171
5 201658
6 201252
7 201739
8 201636
9 201235
10 201730
11 201727
12 201622
13 202222
14 200520
15
Real-time feedback on nonverbal behaviour to enhance social dynamics in small group meetings
200618
16 201818
17 201315
18 201112
19 201712
20 201110

About Jimmy Wang

Jimmy Wang is a scholar working on Electrical and Electronic Engineering, Immunology, Materials Chemistry, Condensed Matter Physics and Biomedical Engineering, having authored 51 papers that have together received 1.0k indexed citations. Recurring topics across this work include Complement system in diseases (9 papers), GaN-based semiconductor devices and materials (7 papers), Organic Light-Emitting Diodes Research (4 papers), Luminescence Properties of Advanced Materials (4 papers), Nanowire Synthesis and Applications (4 papers), Renal Diseases and Glomerulopathies (4 papers), Semiconductor Lasers and Optical Devices (3 papers) and Adenosine and Purinergic Signaling (3 papers). The work is most often cited by research in Health Informatics (29 citations), Nephrology (95 citations), Transplantation (29 citations), Immunology (210 citations) and Endocrinology, Diabetes and Metabolism (129 citations). Jimmy Wang has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Mark Eramian, Ekta Walia, Paul Babyn, Jianning Chi, Gary Groot, Yahsou Delmas, John Kincaid, Wood-Hi Cheng, Chun‐Chin Tsai and Herman Haller. Their work appears in journals such as Blood, Organic Process Research & Development, Nephrology Dialysis Transplantation, Nano Letters and Clinical Kidney Journal.

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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