Aylin Caliskan

4.2k total citations · 2 hit papers
40 papers, 2.0k citations indexed

About

Aylin Caliskan is a scholar working on Artificial Intelligence, Sociology and Political Science and Cognitive Neuroscience. According to data from OpenAlex, Aylin Caliskan has authored 40 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 7 papers in Sociology and Political Science and 5 papers in Cognitive Neuroscience. Recurrent topics in Aylin Caliskan's work include Topic Modeling (9 papers), Hate Speech and Cyberbullying Detection (8 papers) and Authorship Attribution and Profiling (7 papers). Aylin Caliskan is often cited by papers focused on Topic Modeling (9 papers), Hate Speech and Cyberbullying Detection (8 papers) and Authorship Attribution and Profiling (7 papers). Aylin Caliskan collaborates with scholars based in United States, Germany and Netherlands. Aylin Caliskan's co-authors include Joanna J. Bryson, Arvind Narayanan, Robert E. Wolfe, Mahzarin R. Banaji, Tessa Elizabeth Sadie Charlesworth, Rachel Greenstadt, Faisal Ladhak, Tatsunori Hashimoto, Debora Nozza and Federico Bianchi and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Aylin Caliskan

33 papers receiving 1.8k citations

Hit Papers

Semantics derived automatically from language corpora con... 2017 2026 2020 2023 2017 2023 400 800 1.2k
What are hit papers?

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.

  1. Semantics derived automatically from language corpora contain human-like biases
    2017 1.4k citations Aylin Caliskan et al. profile →
  2. Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
    2023 118 citations Federico Bianchi, Pratyusha Kalluri et al. BOA (University of Milano-Bicocca) profile →

Peers

Aylin Caliskan
Angelina McMillan-Major United States
Joy Buolamwini United States
Sanne Kruikemeier Netherlands
René F. Kizilcec United States
Theo Araujo Netherlands
Alexandra Olteanu United States
Andrea L. Guzman United States
Mike Ananny United States
Motahhare Eslami United States
Dirk Hovy Italy
Angelina McMillan-Major United States
Aylin Caliskan
Citations per year, relative to Aylin Caliskan Aylin Caliskan (= 1×) peers Angelina McMillan-Major

Countries citing papers authored by Aylin Caliskan

Since Specialization
Citations

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

Fields of papers citing papers by Aylin Caliskan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aylin Caliskan

This figure shows the co-authorship network connecting the top 25 collaborators of Aylin Caliskan. A scholar is included among the top collaborators of Aylin Caliskan 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 Aylin Caliskan. Aylin Caliskan 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.
Caliskan, Aylin, et al.. (2025). No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 8(3). 2692–2704.
2.
Wilson, Kelly Schwind, et al.. (2025). Bias Amplification in Stable Diffusion’s Representation of Stigma Through Skin Tones and Their Homogeneity. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 8(3). 2705–2717.
3.
Çalışkan, Deniz, et al.. (2025). gSELECT: A novel pre-analysis machine-learning library enabling early hypothesis testing and predictive gene selection in single-cell data. Computational and Structural Biotechnology Journal. 27. 3510–3527.
4.
Caliskan, Aylin, et al.. (2024). Global Gallery: The Fine Art of Painting Culture Portraits through Multilingual Instruction Tuning. 6398–6415. 2 indexed citations
5.
Nicolás, Gandalf & Aylin Caliskan. (2024). Directionality and representativeness are differentiable components of stereotypes in large language models. PNAS Nexus. 3(11). pgae493–pgae493. 3 indexed citations
6.
Charlesworth, Tessa Elizabeth Sadie, et al.. (2024). Extracting intersectional stereotypes from embeddings: Developing and validating the Flexible Intersectional Stereotype Extraction procedure. PNAS Nexus. 3(3). pgae089–pgae089. 4 indexed citations
7.
Lehr, Steven A., Aylin Caliskan, S P Liyanage, & Mahzarin R. Banaji. (2024). ChatGPT as Research Scientist: Probing GPT’s capabilities as a Research Librarian, Research Ethicist, Data Generator, and Data Predictor. Proceedings of the National Academy of Sciences. 121(35). e2404328121–e2404328121. 28 indexed citations
8.
Caliskan, Aylin, et al.. (2024). BiasDora: Exploring Hidden Biased Associations in Vision-Language Models. 10439–10455.
9.
Caliskan, Aylin, et al.. (2024). Science communication with generative AI. Nature Human Behaviour. 8(4). 625–627. 14 indexed citations
10.
Caliskan, Aylin, et al.. (2024). “I Don’t See Myself Represented Here at All”: User Experiences of Stable Diffusion Outputs Containing Representational Harms across Gender Identities and Nationalities. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 7. 463–475. 2 indexed citations
11.
Caliskan, Aylin, et al.. (2024). Safeguarding human values: rethinking US law for generative AI’s societal impacts. AI and Ethics. 5(2). 1433–1459. 10 indexed citations
12.
Caliskan, Aylin, et al.. (2024). Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 7. 1578–1590. 9 indexed citations
13.
Wilson, Shomir, et al.. (2024). Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 7. 476–489. 7 indexed citations
14.
15.
Bianchi, Federico, Pratyusha Kalluri, Esin Durmus, et al.. (2023). Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. BOA (University of Milano-Bicocca). 1493–1504. 118 indexed citations breakdown →
16.
Caliskan, Aylin. (2023). Artificial Intelligence, Bias, and Ethics. 7007–7013. 10 indexed citations
17.
18.
Caliskan, Aylin, Seema Dangwal, & Thomas Dandekar. (2023). Metadata integrity in bioinformatics: Bridging the gap between data and knowledge. Computational and Structural Biotechnology Journal. 21. 4895–4913. 7 indexed citations
19.
Caliskan, Aylin, et al.. (2022). Learning to Behave: Improving Covert Channel Security with Behavior-Based Designs. Proceedings on Privacy Enhancing Technologies. 2022(3). 179–199. 2 indexed citations
20.
Caliskan, Aylin, et al.. (2013). From Language to Family and Back: Native Language and Language Family Identification from English Text. North American Chapter of the Association for Computational Linguistics. 32–39. 1 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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