Upol Ehsan
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 1%
- Ethics and Social Impacts of AI
Papers in
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- Artificial Intelligence in Healthcare and Education 9
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- Ethics and Social Impacts of AI 12
- Co-authors
- Mark Riedl (19 shared papers)Qingzi Vera Liao (5 shared papers)Michael J. Muller (2 shared papers)Justin D. Weisz (3 shared papers)Larry Chan (4 shared papers)Brent E. Harrison (4 shared papers)Pradyumna Tambwekar (2 shared papers)Andreas Riener (5 shared papers)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (2 papers)Patterns (2 papers)Neural Computing and Applications (1 paper)First Monday (1 paper)Lecture notes in computer science (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Upol Ehsan
24 papers receiving 1.1k citations
Upol Ehsan's Hit Papers
Peers
Comparison fields: 5 of 94
- Health Informatics 192
- Safety Research 352
- Artificial Intelligence 626
- Human-Computer Interaction 98
- Computer Science Applications 82
Countries citing papers authored by Upol Ehsan
This map shows the geographic impact of Upol Ehsan'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 Upol Ehsan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Upol Ehsan more than expected).
Fields of papers citing papers by Upol Ehsan
This network shows the impact of papers produced by Upol Ehsan. 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 Upol Ehsan. The network helps show where Upol Ehsan may publish in the future.
Co-authors
The 25 scholars most cited alongside Upol Ehsan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Expanding Explainability: Towards Social Transparency in AI systems Hit paper breakdown → | 2021 | 341 |
| 2 | 2019 | 159 | |
| 3 | 2022 | 81 | |
| 4 | 2021 | 78 | |
| 5 | 2018 | 76 | |
| 6 | 2023 | 58 | |
| 7 | 2017 | 58 | |
| 8 | 2024 | 53 | |
| 9 | 2020 | 43 | |
| 10 | 2022 | 27 | |
| 11 | 2024 | 25 | |
| 12 | 2024 | 23 | |
| 13 | 2024 | 20 | |
| 14 | 2023 | 17 | |
| 15 | 2018 | 15 | |
| 16 | 2020 | 10 | |
| 17 | 2024 | 10 | |
| 18 | 2024 | 8 | |
| 19 | 2019 | 4 | |
| 20 | 2024 | 4 |
About Upol Ehsan
Upol Ehsan is a scholar working on Health Informatics, Safety Research, Artificial Intelligence, Computer Science Applications and Human-Computer Interaction, having authored 26 papers that have together received 1.1k indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (17 papers), Ethics and Social Impacts of AI (12 papers), Artificial Intelligence in Healthcare and Education (9 papers), Topic Modeling (5 papers), Reinforcement Learning in Robotics (4 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Evolutionary Algorithms and Applications (2 papers) and Child Development and Digital Technology (2 papers). The work is most often cited by research in Health Informatics (192 citations), Safety Research (352 citations), Artificial Intelligence (626 citations), Human-Computer Interaction (98 citations) and Computer Science Applications (82 citations). Upol Ehsan has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Mark Riedl, Qingzi Vera Liao, Michael J. Muller, Justin D. Weisz, Larry Chan, Brent E. Harrison, Pradyumna Tambwekar, Andreas Riener, Philipp Wintersberger and Hal Daumé. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Patterns, Neural Computing and Applications, First Monday and Lecture notes in computer science.
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.