Natalia Vélez

565 total citations
21 papers, 231 citations indexed

About

Natalia Vélez is a scholar working on Developmental and Educational Psychology, Sociology and Political Science and Cognitive Neuroscience. According to data from OpenAlex, Natalia Vélez has authored 21 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Developmental and Educational Psychology, 5 papers in Sociology and Political Science and 5 papers in Cognitive Neuroscience. Recurrent topics in Natalia Vélez's work include Child and Animal Learning Development (8 papers), Experimental Behavioral Economics Studies (3 papers) and Social and Intergroup Psychology (3 papers). Natalia Vélez is often cited by papers focused on Child and Animal Learning Development (8 papers), Experimental Behavioral Economics Studies (3 papers) and Social and Intergroup Psychology (3 papers). Natalia Vélez collaborates with scholars based in United States, Sweden and Mexico. Natalia Vélez's co-authors include Hyowon Gweon, Mika Asaba, Hilary Richardson, Jorie Koster-Hale, Liane Young, Rebecca Saxe, Samuel J. Gershman, Sophie Bridgers, Fiery Cushman and Brandon Matthew Woo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Natalia Vélez

17 papers receiving 226 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Natalia Vélez United States 8 99 78 74 53 37 21 231
Ali Mahmoodi United Kingdom 7 119 1.2× 29 0.4× 82 1.1× 61 1.2× 40 1.1× 14 266
Adam Morris United States 8 142 1.4× 45 0.6× 41 0.6× 60 1.1× 47 1.3× 18 271
Regina E. Fabry Germany 12 176 1.8× 70 0.9× 82 1.1× 33 0.6× 77 2.1× 30 322
Marc Slors Netherlands 12 165 1.7× 59 0.8× 121 1.6× 36 0.7× 70 1.9× 43 316
Elizabeth Seiver United States 7 69 0.7× 135 1.7× 68 0.9× 52 1.0× 23 0.6× 11 246
Emily Liquin United States 7 77 0.8× 107 1.4× 54 0.7× 77 1.5× 102 2.8× 15 269
Cathal O’Madagain Germany 8 57 0.6× 97 1.2× 60 0.8× 40 0.8× 39 1.1× 17 196
Rhea M. Howard United States 5 181 1.8× 17 0.2× 80 1.1× 42 0.8× 101 2.7× 5 334
Meike Kroneisen Germany 13 405 4.1× 137 1.8× 116 1.6× 87 1.6× 136 3.7× 30 493
Molly Lewis United States 8 53 0.5× 198 2.5× 33 0.4× 17 0.3× 82 2.2× 19 333

Countries citing papers authored by Natalia Vélez

Since Specialization
Citations

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

Fields of papers citing papers by Natalia Vélez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalia Vélez

This figure shows the co-authorship network connecting the top 25 collaborators of Natalia Vélez. A scholar is included among the top collaborators of Natalia Vélez 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 Natalia Vélez. Natalia Vélez 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.
Guo, Xudong, et al.. (2026). Embodied LLM Agents Learn to Cooperate in Organized Teams. IEEE Transactions on Computational Social Systems. 1–17.
2.
Vélez, Natalia, et al.. (2025). People evaluate idle collaborators based on their impact on task efficiency. Cognition. 264. 106200–106200.
3.
Cushman, Fiery, et al.. (2024). People reward others based on their willingness to exert effort. Journal of Experimental Social Psychology. 116. 104699–104699. 2 indexed citations
4.
Vélez, Natalia, et al.. (2024). Optimizing competence in the service of collaboration. Cognitive Psychology. 150. 101653–101653. 4 indexed citations
5.
Vélez, Natalia, et al.. (2024). A Hierarchical Bayesian Model of Adaptive Teaching. Cognitive Science. 48(7). e13477–e13477. 3 indexed citations
6.
Vélez, Natalia, et al.. (2023). Teachers recruit mentalizing regions to represent learners’ beliefs. Proceedings of the National Academy of Sciences. 120(22). e2215015120–e2215015120. 10 indexed citations
7.
Vélez, Natalia, et al.. (2023). How do Humans Overcome Individual Computational Limitations by Working Together?. Cognitive Science. 47(1). e13232–e13232. 3 indexed citations
8.
Vélez, Natalia, et al.. (2023). Collaborative decision making is grounded in representations of other people’s competence and effort.. Journal of Experimental Psychology General. 152(6). 1565–1579. 10 indexed citations
9.
Cushman, Fiery, et al.. (2023). Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks. Cognition. 241. 105609–105609. 10 indexed citations
10.
Vélez, Natalia, et al.. (2023). The PyMVPA BIDS-App: a robust multivariate pattern analysis pipeline for fMRI data. Frontiers in Neuroscience. 17. 1233416–1233416.
11.
Vélez, Natalia, Charley M. Wu, & Fiery Cushman. (2022). Representational exchange in social learning: Blurring the lines between the ritual and instrumental. Behavioral and Brain Sciences. 45. e271–e271. 2 indexed citations
12.
Asaba, Mika, Sophie Bridgers, Teresa García, et al.. (2021). Moderated Online Data-Collection for Developmental Research: Methods and Replications. Frontiers in Psychology. 12. 734398–734398. 35 indexed citations
13.
Vélez, Natalia & Hyowon Gweon. (2021). Learning from other minds: an optimistic critique of reinforcement learning models of social learning. Current Opinion in Behavioral Sciences. 38. 110–115. 40 indexed citations
14.
Vélez, Natalia & Hyowon Gweon. (2020). Preschoolers use minimal statistical information about social groups to infer the preferences and group membership of individuals.. Cognitive Science. 5 indexed citations
15.
Vélez, Natalia, Sophie Bridgers, & Hyowon Gweon. (2019). The rare preference effect: Statistical information influences social affiliation judgments. Cognition. 192. 103994–103994. 15 indexed citations
16.
Vélez, Natalia, et al.. (2018). Consistent but not diagnostic: Preschoolers' intuitions about shared preferences within social groups.. Cognitive Science. 4 indexed citations
17.
Koster-Hale, Jorie, Hilary Richardson, Natalia Vélez, et al.. (2017). Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs. NeuroImage. 161. 9–18. 69 indexed citations
18.
Vélez, Natalia, Sophie Bridgers, & Hyowon Gweon. (2016). Not all overlaps are equal: Social affiliation and rare overlaps of preferences.. Cognitive Science. 3 indexed citations
19.
Vélez, Natalia, et al.. (2010). Fototerapia y otras alternativas terapéuticas para el manejo del vitiligo, diez años de experiencia en el Servicio de Fototerapia del Centro Dermatológico de la Universidad CES. SHILAP Revista de lepidopterología. 18(3). 149–159.
20.
Vélez, Natalia, et al.. (2009). Perfil epidemiológico de oclusión dental en niños que consultan a la Universidad Cooperativa de Colombia. Dialnet (Universidad de la Rioja). 22(1). 9–13. 3 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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