Phillip Wallis
Impact in
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- Sustainability and Climate Change Governance
- Flood Risk Assessment and Management
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- Coastal and Marine Management
Papers in
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- Neural Networks and Applications 2
- Machine Learning and ELM 1
- Machine Learning in Healthcare 1
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- Sustainability and Climate Change Governance 2
- Co-authors
- Peat Leith (2 shared papers)Andrew Harwood (3 shared papers)Karyn Bosomworth (3 shared papers)Ross Wilkinson (1 shared paper)Ron Sacks‐Davis (1 shared paper)Miranda M. Lim (1 shared paper)Alexander Kain (1 shared paper)Padideh Danaee (1 shared paper)
- Journals
- Environmental Science & Policy (2 papers)eCite Digital Repository (University of Tasmania) (1 paper)2022 IEEE International Conference on Image Processing (ICIP) (1 paper)The Florida AI Research Society (1 paper)
- Partner nations
- United StatesAustraliaGermany
In The Last Decade
Phillip Wallis
7 papers receiving 109 citations
Peers
Comparison fields: 5 of 52
- Global and Planetary Change 57
- Management, Monitoring, Policy and Law 19
- Management Science and Operations Research 15
- Sociology and Political Science 42
- General Agricultural and Biological Sciences 8
Countries citing papers authored by Phillip Wallis
This map shows the geographic impact of Phillip Wallis'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 Phillip Wallis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Wallis more than expected).
Fields of papers citing papers by Phillip Wallis
This network shows the impact of papers produced by Phillip Wallis. 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 Phillip Wallis. The network helps show where Phillip Wallis may publish in the future.
Co-authors
The 12 scholars most cited alongside Phillip Wallis, 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 | 2017 | 79 | |
| 2 | 2018 | 19 | |
| 3 | 1989 | 7 | |
| 4 | 2020 | 4 | |
| 5 | Southern slopes information portal report: climate change adaptation information for natural resource planning and implementation | 2015 | 2 |
| 6 | Learning Semantic Relationships from Medical Codes. | 2019 | 1 |
| 7 | 2020 | 1 | |
| 8 | 2022 | 0 |
About Phillip Wallis
Phillip Wallis is a scholar working on Artificial Intelligence, Global and Planetary Change, Computer Networks and Communications, Molecular Biology and Sociology and Political Science, having authored 8 papers that have together received 113 indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Sustainability and Climate Change Governance (2 papers), Machine Learning and ELM (1 paper), Advanced Neural Network Applications (1 paper), demographic modeling and climate adaptation (1 paper), Advanced Database Systems and Queries (1 paper), Obstructive Sleep Apnea Research (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Global and Planetary Change (57 citations), Management, Monitoring, Policy and Law (19 citations), Management Science and Operations Research (15 citations), Sociology and Political Science (42 citations) and General Agricultural and Biological Sciences (8 citations). Phillip Wallis has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Peat Leith, Andrew Harwood, Karyn Bosomworth, Ross Wilkinson, Ron Sacks‐Davis, Miranda M. Lim, Alexander Kain, Padideh Danaee, Xubo Song and Sean Turner. Their work appears in journals such as Environmental Science & Policy, eCite Digital Repository (University of Tasmania), 2022 IEEE International Conference on Image Processing (ICIP) and The Florida AI Research Society.
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.