Ashraf Abdul
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
-
- Explainable Artificial Intelligence (XAI) 3
- Machine Learning in Healthcare 3
- Topic Modeling 3
-
- Software Engineering Research 1
- Expert finding and Q&A systems 1
- Co-authors
- Brian Y. Lim (4 shared papers)Danding Wang (3 shared papers)Qian Yang (2 shared papers)Mohan Kankanhalli (4 shared papers)Jo Vermeulen (1 shared paper)Wei Tsang Ooi (1 shared paper)
- Journals
- ACM Transactions on Internet Technology (2 papers)National University of Singapore (1 paper)
- Partner nations
- SingaporeUnited StatesDenmark
In The Last Decade
Ashraf Abdul
7 papers receiving 917 citations
Ashraf Abdul's Hit Papers
Peers
Comparison fields: 5 of 91
- Health Informatics 173
- Safety Research 304
- Artificial Intelligence 657
- Human-Computer Interaction 85
- General Decision Sciences 28
Countries citing papers authored by Ashraf Abdul
This map shows the geographic impact of Ashraf Abdul'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 Ashraf Abdul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashraf Abdul more than expected).
Fields of papers citing papers by Ashraf Abdul
This network shows the impact of papers produced by Ashraf Abdul. 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 Ashraf Abdul. The network helps show where Ashraf Abdul may publish in the future.
Co-authors
The 6 scholars most cited alongside Ashraf Abdul, 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 | 2019 | 460 | |
| 2 | Trends and Trajectories for Explainable, Accountable and Intelligible Systems Hit paper breakdown → | 2018 | 423 |
| 3 | 2020 | 45 | |
| 4 | Why these Explanations? Selecting Intelligibility Types for Explanation Goals. | 2019 | 16 |
| 5 | 2023 | 6 | |
| 6 | 2017 | 5 | |
| 7 | 2019 | 1 |
About Ashraf Abdul
Ashraf Abdul is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Science Applications and Management Information Systems, having authored 7 papers that have together received 956 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (3 papers), Machine Learning in Healthcare (3 papers), Topic Modeling (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Human Mobility and Location-Based Analysis (1 paper), Complex Network Analysis Techniques (1 paper), Software Engineering Research (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Health Informatics (173 citations), Safety Research (304 citations), Artificial Intelligence (657 citations), Human-Computer Interaction (85 citations) and General Decision Sciences (28 citations). Ashraf Abdul has collaborated with scholars based in Singapore, United States and Denmark. Frequent co-authors include Brian Y. Lim, Danding Wang, Qian Yang, Mohan Kankanhalli, Jo Vermeulen and Wei Tsang Ooi. Their work appears in journals such as ACM Transactions on Internet Technology and National University of Singapore.
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.