This map shows the geographic impact of Roberta Kwok'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 Roberta Kwok with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberta Kwok more than expected).
This network shows the impact of papers produced by Roberta Kwok. 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 Roberta Kwok. The network helps show where Roberta Kwok may publish in the future.
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Roberta Kwok is a scholar working on Biomedical Engineering, Molecular Biology, Sociology and Political Science, Health and Computer Vision and Pattern Recognition, having authored 42 papers that have together received 869 indexed citations. Recurring topics across this work include Genetics, Bioinformatics, and Biomedical Research (3 papers), Scientific Computing and Data Management (2 papers), Species Distribution and Climate Change (2 papers), EEG and Brain-Computer Interfaces (2 papers), Conferences and Exhibitions Management (2 papers), Muscle activation and electromyography studies (2 papers), Biomedical and Engineering Education (2 papers) and Gene Regulatory Network Analysis (1 paper). The work is most often cited by research in Ecological Modeling (49 citations), Statistics, Probability and Uncertainty (50 citations), Information Systems and Management (39 citations), Biophysics (32 citations) and Health (47 citations). Roberta Kwok has collaborated with scholars based in United Kingdom and United States. Their work appears in journals such as Nature 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.