Ángel Alexander Cabrera

673 total citations
8 papers, 174 citations indexed

About

Ángel Alexander Cabrera is a scholar working on Artificial Intelligence, Safety Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ángel Alexander Cabrera has authored 8 papers receiving a total of 174 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Safety Research and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ángel Alexander Cabrera's work include Explainable Artificial Intelligence (XAI) (5 papers), Ethics and Social Impacts of AI (4 papers) and Mobile Crowdsensing and Crowdsourcing (3 papers). Ángel Alexander Cabrera is often cited by papers focused on Explainable Artificial Intelligence (XAI) (5 papers), Ethics and Social Impacts of AI (4 papers) and Mobile Crowdsensing and Crowdsourcing (3 papers). Ángel Alexander Cabrera collaborates with scholars based in United States and Switzerland. Ángel Alexander Cabrera's co-authors include Adam Perer, Jason Hong, Haojian Jin, Haiyi Zhu, Hong Shen, Marco Túlio Ribeiro, Steven M. Drucker, Dominik Moritz, Robert DeLine and Fred Hohman and has published in prestigious journals such as Journal of Experimental Psychology Learning Memory and Cognition, ACM Transactions on Computer-Human Interaction and Proceedings of the ACM on Human-Computer Interaction.

In The Last Decade

Ángel Alexander Cabrera

8 papers receiving 169 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ángel Alexander Cabrera United States 7 94 68 39 25 25 8 174
Mina Lee United States 7 167 1.8× 27 0.4× 27 0.7× 46 1.8× 22 0.9× 11 261
Mehrnoosh Sameki United States 6 126 1.3× 69 1.0× 81 2.1× 17 0.7× 39 1.6× 14 263
Xinru Wang United States 5 190 2.0× 110 1.6× 20 0.5× 13 0.5× 16 0.6× 10 292
Ashwin Kalyan United States 9 150 1.6× 24 0.4× 25 0.6× 27 1.1× 8 0.3× 13 212
Ian Drosos United States 7 67 0.7× 19 0.3× 58 1.5× 84 3.4× 44 1.8× 11 254
Sravana Reddy United States 11 173 1.8× 35 0.5× 27 0.7× 27 1.1× 12 0.5× 18 318
Matthias Kraus Germany 10 187 2.0× 27 0.4× 24 0.6× 9 0.4× 6 0.2× 26 270
Bifei Mao China 4 79 0.8× 73 1.1× 9 0.2× 26 1.0× 8 0.3× 9 207
Jaimie Drozdal United States 6 104 1.1× 12 0.2× 29 0.7× 49 2.0× 48 1.9× 7 220
David Gray Widder United States 9 76 0.8× 125 1.8× 5 0.1× 71 2.8× 41 1.6× 21 256

Countries citing papers authored by Ángel Alexander Cabrera

Since Specialization
Citations

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

Fields of papers citing papers by Ángel Alexander Cabrera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ángel Alexander Cabrera. 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 Ángel Alexander Cabrera. The network helps show where Ángel Alexander Cabrera may publish in the future.

Co-authorship network of co-authors of Ángel Alexander Cabrera

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

All Works

8 of 8 papers shown
1.
Cabrera, Ángel Alexander, et al.. (2023). Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 11(1). 65–76. 5 indexed citations
2.
Lam, Michelle S., et al.. (2023). Supporting User Engagement in Testing, Auditing, and Contesting AI. 556–559. 6 indexed citations
3.
Cabrera, Ángel Alexander, Adam Perer, & Jason Hong. (2023). Improving Human-AI Collaboration With Descriptions of AI Behavior. Proceedings of the ACM on Human-Computer Interaction. 7(CSCW1). 1–21. 26 indexed citations
4.
Cabrera, Ángel Alexander, Marco Túlio Ribeiro, Bongshin Lee, et al.. (2022). What Did My AI Learn? How Data Scientists Make Sense of Model Behavior. ACM Transactions on Computer-Human Interaction. 30(1). 1–27. 21 indexed citations
5.
Cabrera, Ángel Alexander, et al.. (2022). Symphony: Composing Interactive Interfaces for Machine Learning. CHI Conference on Human Factors in Computing Systems. 1–14. 32 indexed citations
6.
Cabrera, Ángel Alexander, et al.. (2021). Discovering and Validating AI Errors With Crowdsourced Failure Reports. Proceedings of the ACM on Human-Computer Interaction. 5(CSCW2). 1–22. 33 indexed citations
7.
Shen, Hong, Haojian Jin, Ángel Alexander Cabrera, et al.. (2020). Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance. Proceedings of the ACM on Human-Computer Interaction. 4(CSCW2). 1–22. 40 indexed citations
8.
Cabrera, Ángel Alexander, et al.. (1996). Language-driven concept learning: Deciphering Jabberwocky.. Journal of Experimental Psychology Learning Memory and Cognition. 22(2). 539–555. 11 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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