Angelina Wang
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Safety Research top 5%
- Control and Systems Engineering
- Sociology and Political Science
- Co-authors
- Olga RussakovskyV. RamaswamySolon BarocasArvind NarayananPieter AbbeelAviv TamarThanard KurutachHanna Wallach
- Topics
- Ethics and Social Impacts of AI (7 papers)Explainable Artificial Intelligence (XAI) (5 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- Proceedings of the National Academy of SciencesPLoS ONEInternational Journal of Computer Vision
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Angelina Wang
19 papers receiving 332 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 151
- Computer Vision and Pattern Recognition 96
- Safety Research 88
- Control and Systems Engineering 43
- Sociology and Political Science 35
Countries citing papers authored by Angelina Wang
This map shows the geographic impact of Angelina Wang'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 Angelina Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angelina Wang more than expected).
Fields of papers citing papers by Angelina Wang
This network shows the impact of papers produced by Angelina Wang. 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 Angelina Wang. The network helps show where Angelina Wang may publish in the future.
Co-authorship network of co-authors of Angelina Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Angelina Wang. A scholar is included among the top collaborators of Angelina Wang 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 Angelina Wang. Angelina Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Explicitly unbiased large language models still form biased associationsbreakdown → | 13 |
| 2 | Large language models that replace human participants can harmfully misportray and flatten identity groupsbreakdown → | 20 |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 8 | |
| 7 | 10 | |
| 8 | 24 | |
| 9 | 12 | |
| 10 | 7 | |
| 11 | 5 | |
| 12 | 10 | |
| 13 | 39 | |
| 14 | 50 | |
| 15 | 24 | |
| 16 | Directional Bias Amplification | 1 |
| 17 | 46 | |
| 18 | 53 | |
| 19 | 21 |
About Angelina Wang
Angelina Wang is a scholar working on Health Informatics, Safety Research and Music, having authored 19 papers that have together received 349 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (7 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Health Informatics (28 citations), Safety Research (88 citations) and Artificial Intelligence (151 citations). Angelina Wang has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Olga Russakovsky, V. Ramaswamy, Solon Barocas, Arvind Narayanan, Pieter Abbeel, Aviv Tamar, Thanard Kurutach, Hanna Wallach, Sayash Kapoor and John P. Dickerson. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and International Journal of Computer Vision.
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.