Weng‐Keen Wong
- Artificial Intelligence top 1%
- Molecular Biology top 10%
- Plant Science top 5%
- Ecological Modeling top 1%
- Epidemiology top 10%
- Co-authors
- Margaret BurnettSimone StumpfTodd KuleszaTodd C. MocklerAndrew MooreRongkun ShenHenry D. PriestDouglas W. Bryant
- Topics
- Anomaly Detection Techniques and Applications (17 papers)Data-Driven Disease Surveillance (13 papers)Species Distribution and Climate Change (10 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Weng‐Keen Wong
61 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Artificial Intelligence 1.3k
- Molecular Biology 798
- Plant Science 466
- Ecological Modeling 363
- Epidemiology 288
Countries citing papers authored by Weng‐Keen Wong
This map shows the geographic impact of Weng‐Keen Wong'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 Weng‐Keen Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weng‐Keen Wong more than expected).
Fields of papers citing papers by Weng‐Keen Wong
This network shows the impact of papers produced by Weng‐Keen Wong. 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 Weng‐Keen Wong. The network helps show where Weng‐Keen Wong may publish in the future.
Co-authorship network of co-authors of Weng‐Keen Wong
This figure shows the co-authorship network connecting the top 25 collaborators of Weng‐Keen Wong. A scholar is included among the top collaborators of Weng‐Keen Wong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weng‐Keen Wong. Weng‐Keen Wong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 36 | |
| 4 | 25 | |
| 5 | Efficient multi-instance learning for activity recognition from time series data using an auto-regressive hidden Markov model | 23 |
| 6 | Discovering Hotspots and Coldspots of Species Richness in eBird Data | 0 |
| 7 | 21 | |
| 8 | 1 | |
| 9 | 64 | |
| 10 | A special issue of Machine Learning | 1 |
| 11 | 37 | |
| 12 | Genome-wide mapping of alternative splicing in Arabidopsis thalianabreakdown → | 743 |
| 13 | 19 | |
| 14 | Markov blanket feature selection for support vector machines | 7 |
| 15 | What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks | 31 |
| 16 | 56 | |
| 17 | Bayesian network anomaly pattern detection for disease outbreaks | 104 |
| 18 | Optimal reinsertion: a new search operator for accelerated and more accurate Bayesian network structure learning | 60 |
| 19 | 48 | |
| 20 | 83 |
About Weng‐Keen Wong
Weng‐Keen Wong is a scholar working on Ecological Modeling, Software and Artificial Intelligence, having authored 64 papers that have together received 3.3k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (17 papers), Data-Driven Disease Surveillance (13 papers) and Species Distribution and Climate Change (10 papers). The work is most often cited by research in Health Informatics (115 citations), Ecological Modeling (363 citations) and Artificial Intelligence (1.3k citations). Weng‐Keen Wong has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Margaret Burnett, Simone Stumpf, Todd Kulesza, Todd C. Mockler, Andrew Moore, Rongkun Shen, Henry D. Priest, Douglas W. Bryant, Samuel E. Fox and Scott A. Givan. Their work appears in journals such as Bioinformatics, Trends in Ecology & Evolution and Global Change Biology.
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.