Danica J. Sutherland

101 total papers · 1.1k total citations
18 papers, 171 citations indexed

About

Danica J. Sutherland is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Danica J. Sutherland has authored 18 papers receiving a total of 171 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Statistics and Probability. Recurrent topics in Danica J. Sutherland's work include Statistical Methods and Inference (4 papers), Gaussian Processes and Bayesian Inference (2 papers) and Advanced Bandit Algorithms Research (2 papers). Danica J. Sutherland is often cited by papers focused on Statistical Methods and Inference (4 papers), Gaussian Processes and Bayesian Inference (2 papers) and Advanced Bandit Algorithms Research (2 papers). Danica J. Sutherland collaborates with scholars based in United States, United Kingdom and Canada. Danica J. Sutherland's co-authors include Jeff Schneider, Barnabás Póczos, Michelle Ntampaka, Hy Trac, Nicholas Battaglia, Liang Xiong, S. Fromenteau, Arthur Gretton, Michael Arbel and Mikołaj Bińkowski and has published in prestigious journals such as The Astrophysical Journal, Journal of Artificial Intelligence Research and Journal of Interprofessional Care.

In The Last Decade

Danica J. Sutherland

14 papers receiving 163 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Danica J. Sutherland	73	64	36	23	20	18	171
J. De Vicente	61 0.8×	53 0.8×	15 0.4×	24 1.0×	3 0.1×	34	200
R. L. Pennington	125 1.7×	46 0.7×	41 1.1×	61 2.7×	8 0.4×	10	206
Ibrahim Almosallam	97 1.3×	51 0.8×	14 0.4×	35 1.5×	14 0.7×	10	184
Kate Storey-Fisher	186 2.5×	30 0.5×	17 0.5×	71 3.1×	4 0.2×	13	228
Michelle Ntampaka	183 2.5×	44 0.7×	23 0.6×	61 2.7×	6 0.3×	15	207
Yu Luo	111 1.5×	51 0.8×	9 0.3×	66 2.9×	42 2.1×	21	269
P. Huijse	103 1.4×	36 0.6×	7 0.2×	48 2.1×	3 0.1×	24	207
P. Aleo	196 2.7×	46 0.7×	14 0.4×	50 2.2×	4 0.2×	17	275
R. C. Thomas	37 0.5×	29 0.5×	16 0.4×	15 0.7×	4 0.2×	19	157
Luigi Malagò	26 0.4×	72 1.1×	17 0.5×	5 0.2×	23 1.1×	22	167

Countries citing papers authored by Danica J. Sutherland

Since Specialization

Citations

This map shows the geographic impact of Danica J. Sutherland'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 Danica J. Sutherland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danica J. Sutherland more than expected).

Fields of papers citing papers by Danica J. Sutherland

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danica J. Sutherland. 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 Danica J. Sutherland. The network helps show where Danica J. Sutherland may publish in the future.

Co-authorship network of co-authors of Danica J. Sutherland

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

All Works

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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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