Signe Redfield

3.9k total citations · 1 hit paper
19 papers, 1.9k citations indexed

About

Signe Redfield is a scholar working on Neurology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Signe Redfield has authored 19 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Neurology, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Signe Redfield's work include Long-Term Effects of COVID-19 (6 papers), Respiratory Support and Mechanisms (3 papers) and Robotic Path Planning Algorithms (3 papers). Signe Redfield is often cited by papers focused on Long-Term Effects of COVID-19 (6 papers), Respiratory Support and Mechanisms (3 papers) and Robotic Path Planning Algorithms (3 papers). Signe Redfield collaborates with scholars based in United States, United Kingdom and Malaysia. Signe Redfield's co-authors include Lisa McCorkell, Jared P. Austin, Hannah Davis, Ryan Low, Athena Akrami, Gina Assaf, Hannah Wei, Yochai Re’em, Paulo Gonçalves and Sandro Rama Fiorini and has published in prestigious journals such as Cell, Ocean Engineering and Robotics and Computer-Integrated Manufacturing.

In The Last Decade

Signe Redfield

15 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Characterizing long COVID in an international cohort: 7 months of symptoms and their impact

2021 1.7k citations Hannah Davis, Gina Assaf et al. EClinicalMedicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Signe Redfield United States	8	1.5k	730	506	457	359	19	1.9k
Óscar J. Pellicer-Valero Spain	14	539 0.4×	266 0.4×	197 0.4×	125 0.3×	155 0.4×	46	937
Maria Rosaria Barillari Italy	24	649 0.4×	227 0.3×	415 0.8×	51 0.1×	82 0.2×	83	2.4k
Marietta Kirchner Germany	18	318 0.2×	155 0.2×	133 0.3×	109 0.2×	168 0.5×	59	1.3k
Giovanni Cammaroto Italy	27	508 0.3×	172 0.2×	357 0.7×	45 0.1×	58 0.2×	124	2.5k
Miloš Ajčević Italy	19	388 0.3×	78 0.1×	61 0.1×	87 0.2×	124 0.3×	90	1.1k
Phang Boon Lim United Kingdom	23	567 0.4×	135 0.2×	166 0.3×	89 0.2×	147 0.4×	114	2.3k
Mohamed Sakel United Kingdom	20	421 0.3×	169 0.2×	42 0.1×	16 0.0×	196 0.5×	65	1.2k
Guillaume Sacco France	17	110 0.1×	95 0.1×	203 0.4×	51 0.1×	220 0.6×	55	1.0k
Shashank Agarwal United States	17	355 0.2×	46 0.1×	107 0.2×	34 0.1×	50 0.1×	67	950
Yee Sien Ng Singapore	23	263 0.2×	40 0.1×	37 0.1×	30 0.1×	276 0.8×	79	1.8k

Countries citing papers authored by Signe Redfield

Since Specialization

Citations

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

Fields of papers citing papers by Signe Redfield

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Signe Redfield

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

All Works

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19 of 19 papers shown

1.

Redfield, Signe, et al.. (2025). Envisioning Telepresence Robots for Long Covid: A Critical Disability Lens. ACM Transactions on Human-Robot Interaction. 15(1). 1–30. 3 indexed citations

2.

Fitzgerald, Megan, Alison K. Cohen, Julia Moore Vogel, et al.. (2024). A call from patient-researchers to advance research on long COVID. Cell. 187(20). 5490–5496. 2 indexed citations

3.

Redfield, Signe, et al.. (2024). Envisioning Mobile Telemanipulator Robots for Long Covid. 488–491. 1 indexed citations

4.

Redfield, Signe, et al.. (2022). Assistive Robots for Long COVID and ME/CFS Support: Challenges and Opportunities. 124–129. 2 indexed citations

5.

Fisher, Michael, et al.. (2022). Verification of Autonomous Systems [TC Spotlight]. IEEE Robotics & Automation Magazine. 29(1). 99–101.

6.

Davis, Hannah, Gina Assaf, Lisa McCorkell, et al.. (2021). Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. EClinicalMedicine. 38. 101019–101019. 1687 indexed citations breakdown →

7.

Davis, Hannah, Gina Assaf, Lisa McCorkell, et al.. (2021). Characterizing Long COVID in an International Cohort: 7 Months of Symptoms and Their Impact. SSRN Electronic Journal. 39 indexed citations

8.

Freitas, Edison Pignaton de, Joanna Isabelle Olszewska, Joel Luís Carbonera, et al.. (2020). Ontological concepts for information sharing in cloud robotics. Journal of Ambient Intelligence and Humanized Computing. 14(5). 4921–4932. 20 indexed citations

9.

Redfield, Signe. (2019). A definition for robotics as an academic discipline. Nature Machine Intelligence. 1(6). 263–264. 8 indexed citations

10.

Schlenoff, Craig, Stephen Balakirsky, Howard Li, et al.. (2019). IEEE RAS Standards Update [Standards]. IEEE Robotics & Automation Magazine. 26(3). 105–111. 1 indexed citations

11.

Fiorini, Sandro Rama, Julita Bermejo–Alonso, Paulo Gonçalves, et al.. (2017). A Suite of Ontologies for Robotics and Automation [Industrial Activities]. IEEE Robotics & Automation Magazine. 24(1). 8–11. 40 indexed citations

12.

Balakirsky, Stephen, Craig Schlenoff, Sandro Rama Fiorini, et al.. (2017). Towards a Robot Task Ontology Standard. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 14 indexed citations

13.

Fiorini, Sandro Rama, Joel Luís Carbonera, Paulo Gonçalves, et al.. (2014). Extensions to the core ontology for robotics and automation. Robotics and Computer-Integrated Manufacturing. 33. 3–11. 42 indexed citations

14.

Stilwell, Daniel J., et al.. (2012). Theory and experimental results for the multiple aspect coverage problem. Ocean Engineering. 54. 51–60. 12 indexed citations

15.

Stilwell, Daniel J., et al.. (2011). A solution to the multiple aspect coverage problem. 7 indexed citations

16.

Redfield, Signe, et al.. (2005). Hypercomplex Fourier transforms applied to detection for side-scan sonar. 4. 2219–2224. 2 indexed citations

17.

Redfield, Signe. (2004). Lane finding using homogeneous groups of cooperating autonomous vehicles. 2. 26–31. 3 indexed citations

18.

Redfield, Signe & J.G. Harris. (2002). The role of massive color quantization in object recognition. 1. 57–60.

19.

Redfield, Signe. (2001). EFFICIENT OBJECT RECOGNITION USING COLOR QUANTIZATION. 1 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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