Joel Janek Dabrowski
- Water Science and Technology top 10%
- Artificial Intelligence
- Environmental Engineering
- Ocean Engineering top 10%
- Aquatic Science top 10%
- Co-authors
- J. P. de VilliersAshfaqur RahmanAndrew W. GeorgeStuart ArnoldMashud RanaDan PagendamJames HiltonConrad Sanderson
- Topics
- Water Quality Monitoring Technologies (7 papers)Bayesian Modeling and Causal Inference (5 papers)Hydrological Forecasting Using AI (5 papers)
- Journals
- Expert Systems with ApplicationsQuarterly Journal of the Royal Meteorological SocietyComputers and Electronics in Agriculture
- Partner nations
- AustraliaSouth Africa
In The Last Decade
Joel Janek Dabrowski
18 papers receiving 278 citations
Peers
Comparison fields: 5 of 80
- Water Science and Technology 109
- Artificial Intelligence 58
- Environmental Engineering 55
- Ocean Engineering 48
- Aquatic Science 31
Countries citing papers authored by Joel Janek Dabrowski
This map shows the geographic impact of Joel Janek Dabrowski'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 Joel Janek Dabrowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joel Janek Dabrowski more than expected).
Fields of papers citing papers by Joel Janek Dabrowski
This network shows the impact of papers produced by Joel Janek Dabrowski. 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 Joel Janek Dabrowski. The network helps show where Joel Janek Dabrowski may publish in the future.
Co-authorship network of co-authors of Joel Janek Dabrowski
This figure shows the co-authorship network connecting the top 25 collaborators of Joel Janek Dabrowski. A scholar is included among the top collaborators of Joel Janek Dabrowski 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 Joel Janek Dabrowski. Joel Janek Dabrowski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 21 | |
| 7 | 22 | |
| 8 | 23 | |
| 9 | 14 | |
| 10 | 39 | |
| 11 | 7 | |
| 12 | 25 | |
| 13 | 17 | |
| 14 | 11 | |
| 15 | 4 | |
| 16 | 45 | |
| 17 | 9 | |
| 18 | 42 |
About Joel Janek Dabrowski
Joel Janek Dabrowski is a scholar working on Water Science and Technology, Environmental Engineering and Global and Planetary Change, having authored 18 papers that have together received 290 indexed citations. Recurring topics across this work include Water Quality Monitoring Technologies (7 papers), Bayesian Modeling and Causal Inference (5 papers) and Hydrological Forecasting Using AI (5 papers). The work is most often cited by research in Water Science and Technology (109 citations), Aquatic Science (31 citations) and Environmental Engineering (55 citations). Joel Janek Dabrowski has collaborated with scholars based in Australia and South Africa. Frequent co-authors include J. P. de Villiers, Ashfaqur Rahman, Andrew W. George, Stuart Arnold, Mashud Rana, Dan Pagendam, James Hilton, Conrad Sanderson, Petra Kuhnert and Matt Adcock. Their work appears in journals such as Expert Systems with Applications, Quarterly Journal of the Royal Meteorological Society and Computers and Electronics in Agriculture.
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.