Richard Wang

157 papers receiving 4.5k citations

Hit Papers

Precision Medicine: Disease Subtyping and Tailored Treatment 2023 · 135 citations
1350+5+10Years since publication50100150200250

Peers

Richard Wang
Comparison fields: 5 of 198
  • Immunology 762
  • Infectious Diseases 574
  • Management Science and Operations Research 357
  • Management Information Systems 239
  • Virology 113
Replace Zan Huang with:
Zan Huang China
Chun‐yang Zhang China
Chun Li China
Ping Luo China
Kenji Tanaka Japan
Ming‐Wei Lin Taiwan
Linda K. Green United States
Le Zhang China
Hans van Vliet Netherlands
Zhi Wei United States
Richard Wang relative to Zan Huang China Zan Huang's profile →
Citations per field
00.5×3.7×
Zan Huang · 1×
Citations per year

Countries citing papers authored by Richard Wang

Since Specialization
Citations

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

Fields of papers citing papers by Richard Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 171 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998347
2 2012297
3
OpenFlow-based server load balancing gone wild
Hit paper breakdown →
2011275
4 1987235
5 2009218
6
Precision Medicine: Disease Subtyping and Tailored Treatment
Hit paper breakdown →
2023135
7 2017131
8 2010108
9 202097
10 201394
11 198492
12 201689
13 201984
14 200583
15 200877
16 197476
17 200870
18 199570
19 201368
20 201467

About Richard Wang

Richard Wang is a scholar working on Molecular Biology, Epidemiology, Immunology, Infectious Diseases and Electrical and Electronic Engineering, having authored 171 papers that have together received 4.8k indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (16 papers), Cerebrovascular and Carotid Artery Diseases (13 papers), Tuberculosis Research and Epidemiology (10 papers), Stroke Rehabilitation and Recovery (7 papers), T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers), Data Management and Algorithms (5 papers) and Microtubule and mitosis dynamics (5 papers). The work is most often cited by research in Immunology (762 citations), Infectious Diseases (574 citations), Management Science and Operations Research (357 citations), Management Information Systems (239 citations) and Virology (113 citations). Richard Wang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Zheng W. Chen, Jennifer Rexford, Donald P. Ballou, Giri Kumar Tayi, Harold L. Pazer, Zhixiang Wang, Crystal Y. Chen, Dan Huang, John Morgan and Ling Shen. Their work appears in journals such as The Journal of Immunology, Advanced Materials, Journal of Virology, PLoS ONE and Proceedings of the National Academy of Sciences.

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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