Dkm Ip

102 papers receiving 4.8k citations

Hit Papers

Respiratory virus shedding in exhaled breath and efficacy of face masks 2020 · 1.5k citations
1.5k202020262022202450010001.5k

Peers

Dkm Ip
Comparison fields: 5 of 171
  • Modeling and Simulation 1.4k
  • Infectious Diseases 1.3k
  • Epidemiology 2.2k
  • General Dentistry 104
  • Pulmonary and Respiratory Medicine 1.4k
Replace Peng Yang with:
Peng Yang China
Wan Yang United States
Jonathan S. Nguyen‐Van‐Tam United Kingdom
Quanyi Wang China
Daniel K. W. Chu Hong Kong
Abrar Ahmad Chughtai Australia
Julian W. Tang United Kingdom
Nancy Leung Hong Kong
WH Seto Hong Kong
Shuo Feng China
Dkm Ip relative to Peng Yang China Peng Yang's profile →
Citations per field
00.5×1.5×
Peng Yang · 1×
Citations per year

Countries citing papers authored by Dkm Ip

Since Specialization
Citations

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

Fields of papers citing papers by Dkm Ip

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Respiratory virus shedding in exhaled breath and efficacy of face masks
Hit paper breakdown →
20201536
2 2013245
3 2010220
4 2010188
5 2010182
6 2012127
7 2016123
8 2010117
9 2012111
10 2015109
11 201998
12 201091
13 201488
14 201380
15 201577
16 201369
17 201366
18 201966
19 201259
20 201558

About Dkm Ip

Dkm Ip is a scholar working on Modeling and Simulation, Epidemiology, Infectious Diseases, Health and Agronomy and Crop Science, having authored 106 papers that have together received 4.9k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (71 papers), Respiratory viral infections research (48 papers), COVID-19 epidemiological studies (31 papers), SARS-CoV-2 and COVID-19 Research (12 papers), Infection Control and Ventilation (10 papers), Vaccine Coverage and Hesitancy (6 papers), Viral Infections and Outbreaks Research (5 papers) and Diabetes and associated disorders (4 papers). The work is most often cited by research in Modeling and Simulation (1.4k citations), Infectious Diseases (1.3k citations), Epidemiology (2.2k citations), General Dentistry (104 citations) and Pulmonary and Respiratory Medicine (1.4k citations). Dkm Ip has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Benjamin J. Cowling, GM Leung, Malik Peiris, Kwok‐Hung Chan, Vicky J. Fang, Nancy Leung, Daniel K. W. Chu, WH Seto, Eunice Y. C. Shiu and Yuguo Li. Their work appears in journals such as The Journal of Infectious Diseases, Clinical Infectious Diseases, PLoS ONE, Nature Communications and Epidemiology and Infection.

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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