S de la Rosa

1.1k total citations
48 papers, 844 citations indexed

About

S de la Rosa is a scholar working on Cognitive Neuroscience, Social Psychology and Human-Computer Interaction. According to data from OpenAlex, S de la Rosa has authored 48 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cognitive Neuroscience, 32 papers in Social Psychology and 10 papers in Human-Computer Interaction. Recurrent topics in S de la Rosa's work include Action Observation and Synchronization (28 papers), Face Recognition and Perception (16 papers) and Visual perception and processing mechanisms (11 papers). S de la Rosa is often cited by papers focused on Action Observation and Synchronization (28 papers), Face Recognition and Perception (16 papers) and Visual perception and processing mechanisms (11 papers). S de la Rosa collaborates with scholars based in Germany, South Korea and United Kingdom. S de la Rosa's co-authors include HH Bülthoff, Cristóbal Curio, Betty J. Mohler, Stephan Streuber, Martin A. Giese, Ekaterina Volkova, Jeanine K. Stefanucci, Michael J. Black, Javier Romero and Martin Breidt and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

S de la Rosa

48 papers receiving 832 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S de la Rosa Germany 17 477 339 252 169 90 48 844
Kwanguk Kim South Korea 18 383 0.8× 204 0.6× 330 1.3× 133 0.8× 106 1.2× 52 993
Michael N. Geuss United States 15 400 0.8× 254 0.7× 252 1.0× 114 0.7× 56 0.6× 34 689
Harold T. Nefs Netherlands 15 409 0.9× 139 0.4× 292 1.2× 115 0.7× 37 0.4× 37 750
Beatriz Rey Solaz Spain 17 308 0.6× 318 0.9× 664 2.6× 193 1.1× 106 1.2× 49 1.3k
David-Paul Pertaub United Kingdom 5 184 0.4× 393 1.2× 518 2.1× 214 1.3× 65 0.7× 6 924
Anke Huckauf Germany 20 620 1.3× 171 0.5× 439 1.7× 152 0.9× 54 0.6× 85 1.0k
Jane Lessiter United Kingdom 7 227 0.5× 258 0.8× 732 2.9× 121 0.7× 99 1.1× 15 1.0k
Dominik Gall Germany 12 264 0.6× 310 0.9× 710 2.8× 66 0.4× 90 1.0× 21 1.0k
Juan Luis Higuera-Trujillo Spain 15 301 0.6× 426 1.3× 304 1.2× 244 1.4× 33 0.4× 43 1.1k
Alessandro Soranzo United Kingdom 12 390 0.8× 163 0.5× 113 0.4× 129 0.8× 53 0.6× 44 635

Countries citing papers authored by S de la Rosa

Since Specialization
Citations

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

Fields of papers citing papers by S de la Rosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S de la Rosa. 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 S de la Rosa. The network helps show where S de la Rosa may publish in the future.

Co-authorship network of co-authors of S de la Rosa

This figure shows the co-authorship network connecting the top 25 collaborators of S de la Rosa. A scholar is included among the top collaborators of S de la Rosa 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 S de la Rosa. S de la Rosa 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.
Rosa, S de la, et al.. (2024). Investigating Drivers’ Awareness of Pedestrians Using Virtual Reality towards Modeling the Impact of External Factors. Reutlingen University Academic Bibliography (Reutlingen University). 3001–3008. 2 indexed citations
2.
Shah, Punit, et al.. (2024). The influence of body posture on facial expression perception in Autism. Scientific Reports. 14(1). 27655–27655. 1 indexed citations
3.
Preston, Catherine, et al.. (2023). Four fundamental dimensions underlie the perception of human actions. Attention Perception & Psychophysics. 86(2). 536–558. 7 indexed citations
4.
Ward, Isobel, Erika P. Raven, S de la Rosa, et al.. (2023). White matter microstructure in face and body networks predicts facial expression and body posture perception across development. Human Brain Mapping. 44(6). 2307–2322. 4 indexed citations
5.
Rosa, S de la, et al.. (2017). Comparing Individual and Collaborative Problem Solving in Environmental Search. Cognitive Science. 650–650. 1 indexed citations
6.
Ferstl, Ylva, HH Bülthoff, & S de la Rosa. (2017). Action recognition is sensitive to the identity of the actor. Cognition. 166. 201–206. 14 indexed citations
7.
Bülthoff, I, et al.. (2017). Action recognition is viewpoint-dependent in the visual periphery. Vision Research. 135. 10–15. 4 indexed citations
8.
Bülthoff, HH, et al.. (2017). Cultural differences in room size perception. PLoS ONE. 12(4). e0176115–e0176115. 18 indexed citations
9.
Longo, Matthew R., et al.. (2016). The role of visual similarity and memory in body model distortions. Acta Psychologica. 164. 103–111. 32 indexed citations
10.
Rosa, S de la, Ylva Ferstl, & HH Bülthoff. (2016). Visual adaptation dominates bimodal visual-motor action adaptation. Scientific Reports. 6(1). 23829–23829. 7 indexed citations
11.
Rosa, S de la, et al.. (2016). fMRI Adaptation between Action Observation and Action Execution Reveals Cortical Areas with Mirror Neuron Properties in Human BA 44/45. Frontiers in Human Neuroscience. 10. 78–78. 20 indexed citations
12.
Bülthoff, HH, et al.. (2015). Objects exhibit body model like shape distortions. Experimental Brain Research. 233(5). 1471–1479. 38 indexed citations
13.
Volkova, Ekaterina, S de la Rosa, HH Bülthoff, & Betty J. Mohler. (2014). The MPI Emotional Body Expressions Database for Narrative Scenarios. PLoS ONE. 9(12). e113647–e113647. 52 indexed citations
14.
Rosa, S de la, et al.. (2014). Visual categorization of social interactions. Visual Cognition. 22(9-10). 1233–1271. 15 indexed citations
15.
Rosa, S de la, et al.. (2013). View dependencies in the visual recognition of social interactions. SHILAP Revista de lepidopterología. 172 indexed citations
16.
Rosa, S de la, Martin A. Giese, HH Bülthoff, & Cristóbal Curio. (2013). The contribution of different cues of facial movement to the emotional facial expression adaptation aftereffect. Journal of Vision. 13(1). 23–23. 17 indexed citations
17.
Rosa, S de la, et al.. (2010). Visual object detection, categorization, and identification tasks are associated with different time courses and sensitivities.. Journal of Experimental Psychology Human Perception & Performance. 37(1). 38–47. 21 indexed citations
18.
Streuber, Stephan & S de la Rosa. (2009). The role of body and tool-based information in joint action coordination. MPG.PuRe (Max Planck Society). 33. 1 indexed citations
19.
Rosa, S de la, Michael Gordon, & Bruce A. Schneider. (2009). Knowledge alters visual contrast sensitivity. Attention Perception & Psychophysics. 71(3). 451–462. 6 indexed citations
20.
Rosa, S de la, Giampaolo Moraglia, & Bruce A. Schneider. (2008). The magnitude of binocular disparity modulates search time for targets defined by a conjunction of depth and colour.. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale. 62(3). 150–155. 15 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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