Sarah Tan

37 total papers · 635 total citations
11 papers, 120 citations indexed

About

Sarah Tan is a scholar working on Artificial Intelligence, Statistics and Probability and Biomedical Engineering. According to data from OpenAlex, Sarah Tan has authored 11 papers receiving a total of 120 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 2 papers in Statistics and Probability and 2 papers in Biomedical Engineering. Recurrent topics in Sarah Tan's work include Explainable Artificial Intelligence (XAI) (8 papers), Machine Learning and Data Classification (7 papers) and Adversarial Robustness in Machine Learning (6 papers). Sarah Tan is often cited by papers focused on Explainable Artificial Intelligence (XAI) (8 papers), Machine Learning and Data Classification (7 papers) and Adversarial Robustness in Machine Learning (6 papers). Sarah Tan collaborates with scholars based in United States, Canada and Austria. Sarah Tan's co-authors include Rich Caruana, Giles Hooker, Paul Koch, Chun‐Hao Chang, Anna Goldenberg, Martin T. Wells, Albert Gordo, Yin Lou, Xuezhou Zhang and Urszula Chajewska and has published in prestigious journals such as Machine Learning, Electrophoresis and arXiv (Cornell University).

In The Last Decade

Sarah Tan

9 papers receiving 114 citations

Author Peers

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

Author						Papers	Cites
Sarah Tan	83	18	8	6	6	11	120
Simon Ott	56 0.7×	16 0.9×	4 0.5×	13 2.2×	7 1.2×	12	121
Haoxuan Che	112 1.3×	5 0.3×	7 0.9×	8 1.3×	13 2.2×	9	142
David Froelicher	160 1.9×	16 0.9×	5 0.6×	20 3.3×	12 2.0×	11	214
Natalie Dullerud	69 0.8×	15 0.8×	4 0.5×	4 0.7×	11 1.8×	7	90
Arav Agarwal	39 0.5×	31 1.7×	5 0.6×	12 2.0×	4 0.7×	9	143
Potsawee Manakul	129 1.6×	16 0.9×		4 0.7×	8 1.3×	13	166
Katherine A. Keith	98 1.2×	3 0.2×	9 1.1×	7 1.2×	20 3.3×	9	242
Michael Muelly	167 2.0×	13 0.7×	7 0.9×	12 2.0×	51 8.5×	13	256
Niyaz Ahmad Wani	121 1.5×	26 1.4×	14 1.8×	11 1.8×	27 4.5×	15	241
Lameck Mbangula Amugongo	29 0.3×	36 2.0×	16 2.0×	5 0.8×	5 0.8×	12	116

Countries citing papers authored by Sarah Tan

Since Specialization

Citations

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

Fields of papers citing papers by Sarah Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sarah Tan. 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 Sarah Tan. The network helps show where Sarah Tan may publish in the future.

Co-authorship network of co-authors of Sarah Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Tan. A scholar is included among the top collaborators of Sarah Tan 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 Sarah Tan. Sarah Tan 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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