Phillip Wallis

2.6k total citations
7 papers, 109 citations indexed

About

Phillip Wallis is a scholar working on Artificial Intelligence, Global and Planetary Change and Computer Networks and Communications. According to data from OpenAlex, Phillip Wallis has authored 7 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Global and Planetary Change and 1 paper in Computer Networks and Communications. Recurrent topics in Phillip Wallis's work include Sustainability and Climate Change Governance (2 papers), Pasture and Agricultural Systems (1 paper) and Neural Networks and Applications (1 paper). Phillip Wallis is often cited by papers focused on Sustainability and Climate Change Governance (2 papers), Pasture and Agricultural Systems (1 paper) and Neural Networks and Applications (1 paper). Phillip Wallis collaborates with scholars based in Australia and United States. Phillip Wallis's co-authors include Karyn Bosomworth, Peat Leith, Andrew Harwood, Ross Wilkinson, Ron Sacks‐Davis, Padideh Danaee, Xubo Song, Miranda M. Lim, Alexander Kain and Rebecca M. B. Harris and has published in prestigious journals such as Environmental Science & Policy, eCite Digital Repository (University of Tasmania) and The Florida AI Research Society.

In The Last Decade

Phillip Wallis

6 papers receiving 106 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Phillip Wallis Australia	4	57	42	19	15	12	7	109
Pongchai Dumrongrojwatthana Thailand	6	76 1.3×	20 0.5×	19 1.0×	21 1.4×	13 1.1×	22	153
Eirini Skrimizea Belgium	8	45 0.8×	56 1.3×	19 1.0×	8 0.5×	19 1.6×	10	151
Leanne Scott South Africa	5	49 0.9×	19 0.5×	13 0.7×	26 1.7×	7 0.6×	15	143
Glenn G. Page United States	5	36 0.6×	25 0.6×	31 1.6×	13 0.9×	4 0.3×	11	111
Hugo Herrera Norway	6	41 0.7×	30 0.7×	7 0.4×	47 3.1×	26 2.2×	10	171
Asha Sitati United States	3	66 1.2×	78 1.9×	15 0.8×	3 0.2×	19 1.6×	3	126
Gary Kass United Kingdom	4	26 0.5×	25 0.6×	11 0.6×	9 0.6×	3 0.3×	9	88
Iain Dillingham United Kingdom	4	36 0.6×	20 0.5×	17 0.9×	5 0.3×	5 0.4×	6	90
Kazuhiko Ota Japan	6	37 0.6×	29 0.7×	21 1.1×	9 0.6×	5 0.4×	6	108
Alexander Gardner Australia	7	45 0.8×	23 0.5×	31 1.6×	5 0.3×	5 0.4×	51	229

Countries citing papers authored by Phillip Wallis

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Phillip Wallis

This figure shows the co-authorship network connecting the top 25 collaborators of Phillip Wallis. A scholar is included among the top collaborators of Phillip Wallis 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 Phillip Wallis. Phillip Wallis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Wallis, Phillip & Xubo Song. (2022). Efficient Fine-Tuning of Deep Neural Networks with Effective Parameter Allocation. 2022 IEEE International Conference on Image Processing (ICIP). 3510–3514.

2.

Wallis, Phillip, et al.. (2020). Automatic Event Detection of REM Sleep Without Atonia From Polysomnography Signals Using Deep Neural Networks. 4112–4116. 4 indexed citations

3.

Wallis, Phillip & Padideh Danaee. (2019). Learning Semantic Relationships from Medical Codes.. The Florida AI Research Society. 305–310. 1 indexed citations

4.

Leith, Peat, et al.. (2018). An operation on ‘the neglected heart of science policy’: Reconciling supply and demand for climate change adaptation research. Environmental Science & Policy. 82. 117–125. 18 indexed citations

5.

Bosomworth, Karyn, Peat Leith, Andrew Harwood, & Phillip Wallis. (2017). What’s the problem in adaptation pathways planning? The potential of a diagnostic problem-structuring approach. Environmental Science & Policy. 76. 23–28. 77 indexed citations

6.

Wallis, Phillip, Andrew Harwood, Karyn Bosomworth, et al.. (2015). Southern slopes information portal report: climate change adaptation information for natural resource planning and implementation. eCite Digital Repository (University of Tasmania). 2 indexed citations

7.

Sacks‐Davis, Ron, Phillip Wallis, & Ross Wilkinson. (1989). Using syntactic analysis in a document retrieval system that uses signature files. 179–192. 7 indexed citations

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.

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