Richard K. Kiang
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies 6
-
- Influenza Virus Research Studies 8
- Infectious Diseases top 10%
- Viral Infections and Vectors 4
-
- Neural Networks and Applications 4
-
- Remote Sensing in Agriculture 3
-
- Remote-Sensing Image Classification 3
-
- Particle physics theoretical and experimental studies 3
-
- Climate variability and models 3
- Co-authors
- Radina P. SoebiyantoFarida AdimiNajibullah SafiMarc‐Alain WiddowsonJorge JaraEduardo Azziz‐BaumgartnerLeticia CastilloAlexey Clara
- Journals
- Physical Review Letters (1 paper)SHILAP Revista de lepidopterología (1 paper)PLoS ONE (4 papers)
- Partner nations
- United StatesGermanyGuatemala
In The Last Decade
Richard K. Kiang
25 papers receiving 531 citations
Peers
Comparison fields: 5 of 108
- Modeling and Simulation 208
- Epidemiology 242
- Infectious Diseases 127
- Health, Toxicology and Mutagenesis 70
- Public Health, Environmental and Occupational Health 103
Countries citing papers authored by Richard K. Kiang
This map shows the geographic impact of Richard K. Kiang'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 K. Kiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard K. Kiang more than expected).
Fields of papers citing papers by Richard K. Kiang
This network shows the impact of papers produced by Richard K. Kiang. 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 K. Kiang. The network helps show where Richard K. Kiang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Richard K. Kiang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 11 | |
| 2 | 2015 | 23 | |
| 3 | 2015 | 44 | |
| 4 | Using Earth Observations to Understand and Predict Infectious Diseases | 2015 | 0 |
| 5 | 2014 | 70 | |
| 6 | 2013 | 2 | |
| 7 | Towards Global Characterization of Environmental and Climatic Determinants for Seasonal Influenza | 2011 | 1 |
| 8 | 2010 | 161 | |
| 9 | 2010 | 56 | |
| 10 | Modeling Influenza Transmission Using Environmental Parameters | 2010 | 6 |
| 11 | 2006 | 49 | |
| 12 | 2005 | 2 | |
| 13 | Conceptual Study of Intelligent Data Archives of the Future | 2002 | 1 |
| 14 | 1997 | 3 | |
| 15 | Handwritten character recognition using neural network architectures | 1990 | 19 |
| 16 | 1987 | 12 | |
| 17 | 1982 | 7 | |
| 18 | Atmospheric effects on cluster analyses | 1979 | 1 |
| 19 | Monitoring Earth Albedo from LANDSAT | 1977 | 1 |
| 20 | 1973 | 13 |
About Richard K. Kiang
Richard K. Kiang is a scholar working on Modeling and Simulation, Media Technology and Epidemiology, having authored 29 papers that have together received 551 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (8 papers), COVID-19 epidemiological studies (6 papers), Neural Networks and Applications (4 papers), Viral Infections and Vectors (4 papers), Remote Sensing in Agriculture (3 papers), Remote-Sensing Image Classification (3 papers), Particle physics theoretical and experimental studies (3 papers) and Climate variability and models (3 papers). The work is most often cited by research in Modeling and Simulation (208 citations), Epidemiology (242 citations) and Infectious Diseases (127 citations). Richard K. Kiang has collaborated with scholars based in United States, Germany and Guatemala. Frequent co-authors include Radina P. Soebiyanto, Farida Adimi, Najibullah Safi, Marc‐Alain Widdowson, Jorge Jara, Eduardo Azziz‐Baumgartner, Leticia Castillo, Alexey Clara, Brian A. Telfer and James G. Acker. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and PLoS ONE.
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.