Arjun Subramonian
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Hate Speech and Cyberbullying Detection
- Safety Research top 10%
- Ethics and Social Impacts of AI
Papers in
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- Hate Speech and Cyberbullying Detection 3
- Natural Language Processing Techniques 3
- Topic Modeling 2
- Text Readability and Simplification 2
- Advanced Graph Neural Networks 2
- Adversarial Robustness in Machine Learning 1
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- Ethics and Social Impacts of AI 3
- Co-authors
- Kai-Wei Chang (2 shared papers)Anaelia Ovalle (3 shared papers)Jeff M. Phillips (1 shared paper)Sunipa Dev (1 shared paper)Yizhou Sun (1 shared paper)Ziniu Hu (1 shared paper)Gilbert C. Gee (1 shared paper)Rowena Garcia (1 shared paper)
- Journals
- The Astronomical Journal (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)XRDS Crossroads The ACM Magazine for Students (1 paper)
- Partner nations
- United StatesGermanyHong Kong
In The Last Decade
Arjun Subramonian
10 papers receiving 171 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 121
- Safety Research 29
- General Social Sciences 7
- Health Informatics 2
- Gender Studies 10
Countries citing papers authored by Arjun Subramonian
This map shows the geographic impact of Arjun Subramonian'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 Arjun Subramonian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arjun Subramonian more than expected).
Fields of papers citing papers by Arjun Subramonian
This network shows the impact of papers produced by Arjun Subramonian. 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 Arjun Subramonian. The network helps show where Arjun Subramonian may publish in the future.
Co-authors
The 25 scholars most cited alongside Arjun Subramonian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 81 | |
| 2 | 2021 | 42 | |
| 3 | 2023 | 17 | |
| 4 | 2024 | 14 | |
| 5 | 2023 | 10 | |
| 6 | 2023 | 7 | |
| 7 | 2020 | 4 | |
| 8 | 2023 | 3 | |
| 9 | 2022 | 1 | |
| 10 | 2021 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2024 | 0 |
About Arjun Subramonian
Arjun Subramonian is a scholar working on Artificial Intelligence, Safety Research, Statistical and Nonlinear Physics, General Health Professions and Astronomy and Astrophysics, having authored 12 papers that have together received 180 indexed citations. Recurring topics across this work include Hate Speech and Cyberbullying Detection (3 papers), Natural Language Processing Techniques (3 papers), Ethics and Social Impacts of AI (3 papers), Topic Modeling (2 papers), Text Readability and Simplification (2 papers), Advanced Graph Neural Networks (2 papers), Complex Network Analysis Techniques (2 papers) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Artificial Intelligence (121 citations), Safety Research (29 citations), General Social Sciences (7 citations), Health Informatics (2 citations) and Gender Studies (10 citations). Arjun Subramonian has collaborated with scholars based in United States, Germany and Hong Kong. Frequent co-authors include Kai-Wei Chang, Anaelia Ovalle, Jeff M. Phillips, Sunipa Dev, Yizhou Sun, Ziniu Hu, Gilbert C. Gee, Rowena Garcia, Avijit Ghosh and Skyler Wang. Their work appears in journals such as The Astronomical Journal, IEEE Transactions on Knowledge and Data Engineering, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the AAAI Conference on Artificial Intelligence and XRDS Crossroads The ACM Magazine for Students.
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.