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.
Countries citing papers authored by Cynthia Breazeal
Since
Specialization
Citations
This map shows the geographic impact of Cynthia Breazeal'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 Cynthia Breazeal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cynthia Breazeal more than expected).
Fields of papers citing papers by Cynthia Breazeal
This network shows the impact of papers produced by Cynthia Breazeal. 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 Cynthia Breazeal. The network helps show where Cynthia Breazeal may publish in the future.
Co-authorship network of co-authors of Cynthia Breazeal
This figure shows the co-authorship network connecting the top 25 collaborators of Cynthia Breazeal.
A scholar is included among the top collaborators of Cynthia Breazeal 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 Cynthia Breazeal. Cynthia Breazeal is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ali, Safinah, et al.. (2024). Constructing Dreams Using Generative AI. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23268–23275.25 indexed citations
Touretzky, David S., Christina Gardner‐McCune, Cynthia Breazeal, Fred Martin, & Deborah Seehorn. (2019). A Year in K–12 AI Education. AI Magazine. 40(4). 88–90.64 indexed citations
8.
Bailey, Alison L., et al.. (2019). A robotic interface for the administration of language, literacy, and speech pathology assessments for children.. 41–42.4 indexed citations
Lee, Jin Joo, et al.. (2013). Modeling the Dynamics of Nonverbal Behavior on Interpersonal Trust for Human-Robot Interactions. DSpace@MIT (Massachusetts Institute of Technology).11 indexed citations
11.
Shah, Julie, Brian Williams, & Cynthia Breazeal. (2010). Dynamic Execution of Temporal Plans for Temporally Fluid Human-Robot Teaming.. National Conference on Artificial Intelligence.1 indexed citations
12.
Breazeal, Cynthia & Matt Berlin. (2008). Spatial scaffolding for sociable robot learning. National Conference on Artificial Intelligence. 1268–1273.4 indexed citations
13.
Hoffman, Guy & Cynthia Breazeal. (2008). Anticipatory perceptual simulation for human-robot joint practice: theory and application study. National Conference on Artificial Intelligence. 1357–1362.16 indexed citations
14.
Kidd, Cory D. & Cynthia Breazeal. (2007). A robotic weight loss coach. National Conference on Artificial Intelligence. 1985–1986.44 indexed citations
15.
Berlin, Matt, et al.. (2006). Perspective taking: an organizing principle for learning in human-robot interaction. National Conference on Artificial Intelligence. 1444–1450.48 indexed citations
16.
Hoffman, Guy & Cynthia Breazeal. (2006). What Lies Ahead? Expectation Management in Human-Robot Collaboration.. National Conference on Artificial Intelligence. 1–7.2 indexed citations
Breazeal, Cynthia, Daphna Buchsbaum, Jesse Gray, & Bruce Blumberg. (2003). Learning From and About Others: Towards Using Imitation to Bootstrap the Social Competence of Robots. 72(4). 935–9.4 indexed citations
19.
Breazeal, Cynthia & Brian Scassellati. (2002). Robots that imitate humans. Trends in Cognitive Sciences. 6(11). 481–487.277 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.