Austin Wang
Impact in
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- Cryptography and Data Security
- Privacy-Preserving Technologies in Data
Papers in
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- Multimodal Machine Learning Applications 3
- Human Pose and Action Recognition 2
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- Privacy-Preserving Technologies in Data 4
- Cryptography and Data Security 3
- Adversarial Robustness in Machine Learning 2
- Co-authors
- Raylin TsoYu‐Chi ChenKurt GrayDinesh ManochaAniket BeraSiying ChenTanmay RandhavaneFerran Altarriba Bertran
- Journals
- Journal of Intensive Care Medicine (1 paper)Journal of Information Security and Applications (1 paper)Future Generation Computer Systems (1 paper)Alzheimer s Research & Therapy (1 paper)American Journal of Physical Medicine & Rehabilitation (1 paper)
- Partner nations
- United StatesTaiwanAustralia
In The Last Decade
Austin Wang
21 papers receiving 153 citations
Peers
Comparison fields: 5 of 75
- Human Factors and Ergonomics 6
- Artificial Intelligence 43
- Internal Medicine 5
- Human-Computer Interaction 7
- Communication 8
Countries citing papers authored by Austin Wang
This map shows the geographic impact of Austin 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 Austin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Austin Wang more than expected).
Fields of papers citing papers by Austin Wang
This network shows the impact of papers produced by Austin 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 Austin Wang. The network helps show where Austin Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Austin Wang, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 14 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 8 | |
| 7 | 2022 | 3 | |
| 8 | 2022 | 1 | |
| 9 | 2021 | 22 | |
| 10 | 2021 | 31 | |
| 11 | 2020 | 19 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 4 | |
| 14 | 2020 | 1 | |
| 15 | 2020 | 7 | |
| 16 | 2019 | 3 | |
| 17 | 2019 | 16 | |
| 18 | 2016 | 5 | |
| 19 | 2015 | 2 | |
| 20 | 2015 | 1 |
About Austin Wang
Austin Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Information Systems and Transportation, having authored 24 papers that have together received 159 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (4 papers), Cryptography and Data Security (3 papers), Multimodal Machine Learning Applications (3 papers), Social Robot Interaction and HRI (2 papers), Human Pose and Action Recognition (2 papers), Cloud Data Security Solutions (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Child Development and Digital Technology (2 papers). The work is most often cited by research in Human Factors and Ergonomics (6 citations), Artificial Intelligence (43 citations), Internal Medicine (5 citations), Human-Computer Interaction (7 citations) and Communication (8 citations). Austin Wang has collaborated with scholars based in United States, Taiwan and Australia. Frequent co-authors include Raylin Tso, Yu‐Chi Chen, Kurt Gray, Dinesh Manocha, Aniket Bera, Siying Chen, Tanmay Randhavane, Ferran Altarriba Bertran, Sri Kurniawan and Katherine Isbister. Their work appears in journals such as Journal of Intensive Care Medicine, Journal of Information Security and Applications, Future Generation Computer Systems, Alzheimer s Research & Therapy and American Journal of Physical Medicine & Rehabilitation.
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.