Olivia S. Cheung

1.1k total citations
30 papers, 645 citations indexed

About

Olivia S. Cheung is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Olivia S. Cheung has authored 30 papers receiving a total of 645 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 18 papers in Experimental and Cognitive Psychology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Olivia S. Cheung's work include Face Recognition and Perception (21 papers), Evolutionary Psychology and Human Behavior (12 papers) and Neural and Behavioral Psychology Studies (7 papers). Olivia S. Cheung is often cited by papers focused on Face Recognition and Perception (21 papers), Evolutionary Psychology and Human Behavior (12 papers) and Neural and Behavioral Psychology Studies (7 papers). Olivia S. Cheung collaborates with scholars based in United States, United Arab Emirates and Hong Kong. Olivia S. Cheung's co-authors include L. Gauthier, Jennifer J. Richler, Moshe Bar, Matthew F. Panichello, Alan C.‐N. Wong, William G. Hayward, Chenxi He, Rachel Wu, Wei Chen and Webb Phillips and has published in prestigious journals such as Journal of Neuroscience, Scientific Reports and Psychological Science.

In The Last Decade

Olivia S. Cheung

28 papers receiving 629 citations

Author Peers

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

Author Last Decade Papers Cites
Olivia S. Cheung 578 274 157 90 58 30 645
Rankin W. McGugin 667 1.2× 232 0.8× 221 1.4× 68 0.8× 67 1.2× 32 740
Timothy J. Vickery 540 0.9× 163 0.6× 88 0.6× 93 1.0× 54 0.9× 30 647
Vadim Axelrod 719 1.2× 258 0.9× 136 0.9× 60 0.7× 24 0.4× 28 787
Lizann Bonnar 380 0.7× 150 0.5× 133 0.8× 49 0.5× 58 1.0× 6 449
Luc Boutsen 472 0.8× 154 0.6× 110 0.7× 62 0.7× 23 0.4× 15 514
Edwin Burns 399 0.7× 188 0.7× 152 1.0× 57 0.6× 71 1.2× 26 447
Rebecca F. Schwarzlose 658 1.1× 169 0.6× 100 0.6× 158 1.8× 51 0.9× 17 738
Diana Omigie 617 1.1× 222 0.8× 51 0.3× 133 1.5× 57 1.0× 41 678
Allan McNeill 442 0.8× 239 0.9× 246 1.6× 94 1.0× 19 0.3× 9 521
John Towler 606 1.0× 425 1.6× 224 1.4× 61 0.7× 36 0.6× 23 693

Countries citing papers authored by Olivia S. Cheung

Since Specialization
Citations

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

Fields of papers citing papers by Olivia S. Cheung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olivia S. Cheung. 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 Olivia S. Cheung. The network helps show where Olivia S. Cheung may publish in the future.

Co-authorship network of co-authors of Olivia S. Cheung

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

All Works

20 of 20 papers shown
1.
Cheung, Olivia S., et al.. (2024). Implicit bias and experience influence overall but not relative trustworthiness judgment of other-race faces. Scientific Reports. 14(1). 16068–16068. 1 indexed citations
2.
Hayward, William G., et al.. (2024). Two faces of holistic face processing: Facilitation and interference underlying part-whole and composite effects. Journal of Vision. 24(11). 13–13.
3.
Cheung, Olivia S., et al.. (2024). Facilitation and interference are asymmetric in holistic face processing. Psychonomic Bulletin & Review. 31(5). 2214–2225. 3 indexed citations
4.
Cheung, Olivia S., et al.. (2023). Effects of masculinity vs. femininity on competence judgement of politician faces and election outcome prediction. Scientific Reports. 13(1). 16825–16825.
5.
Chen, Wei, et al.. (2023). The role of implicit social bias on holistic processing of out-group faces. Cognitive Research Principles and Implications. 8(1). 7–7. 1 indexed citations
6.
He, Chenxi, et al.. (2021). Rapid category selectivity for animals versus man-made objects: An N2pc study. International Journal of Psychophysiology. 171. 20–28. 3 indexed citations
7.
Cheung, Olivia S., et al.. (2021). The effect of implicit racial bias on recognition of other-race faces. Cognitive Research Principles and Implications. 6(1). 67–67. 15 indexed citations
8.
He, Chenxi, et al.. (2020). Roles of Category, Shape, and Spatial Frequency in Shaping Animal and Tool Selectivity in the Occipitotemporal Cortex. Journal of Neuroscience. 40(29). 5644–5657. 12 indexed citations
9.
Wu, Rachel, et al.. (2016). Increased experience amplifies the activation of task-irrelevant category representations. Attention Perception & Psychophysics. 79(2). 522–532. 13 indexed citations
10.
Cheung, Olivia S. & L. Gauthier. (2014). Visual appearance interacts with conceptual knowledge in object recognition. Frontiers in Psychology. 5. 793–793. 12 indexed citations
11.
Panichello, Matthew F., Olivia S. Cheung, & Moshe Bar. (2013). Predictive Feedback and Conscious Visual Experience. Frontiers in Psychology. 3. 620–620. 91 indexed citations
12.
Cheung, Olivia S., Sylvain Gagnon, Matthew F. Panichello, & Moshe Bar. (2012). Dissociating contextual and semantic priming in object recognition. Journal of Vision. 12(9). 813–813. 1 indexed citations
13.
Cheung, Olivia S. & Moshe Bar. (2011). Visual prediction and perceptual expertise. International Journal of Psychophysiology. 83(2). 156–163. 27 indexed citations
14.
Richler, Jennifer J., Olivia S. Cheung, & L. Gauthier. (2011). Beliefs alter holistic face processing ... if response bias is not taken into account. Journal of Vision. 11(13). 17–17. 45 indexed citations
15.
Cheung, Olivia S., Jennifer J. Richler, Webb Phillips, & L. Gauthier. (2011). Does temporal integration of face parts reflect holistic processing?. Psychonomic Bulletin & Review. 18(3). 476–483. 12 indexed citations
16.
Cheung, Olivia S. & L. Gauthier. (2010). Selective interference on the holistic processing of faces in working memory.. Journal of Experimental Psychology Human Perception & Performance. 36(2). 448–461. 21 indexed citations
17.
Gauthier, L., Jennifer J. Richler, & Olivia S. Cheung. (2010). Beliefs alone alter holistic face processing...If response bias is not taken into account. Journal of Vision. 10(7). 679–679. 2 indexed citations
18.
Richler, Jennifer J., Olivia S. Cheung, Alan C.‐N. Wong, & L. Gauthier. (2009). Does response interference contribute to face composite effects?. Psychonomic Bulletin & Review. 16(2). 258–263. 27 indexed citations
19.
Cheung, Olivia S., William G. Hayward, & L. Gauthier. (2009). Dissociating the effects of angular disparity and image similarity in mental rotation and object recognition. Cognition. 113(1). 128–133. 15 indexed citations
20.
Gauthier, L., Alan C.‐N. Wong, William G. Hayward, & Olivia S. Cheung. (2006). Font Tuning Associated with Expertise in Letter Perception. Perception. 35(4). 541–559. 41 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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