Eric Wong
Impact in
- Artificial Intelligence top 10%
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Natural Language Processing Techniques
- Health Information Management top 10%
- Electronic Health Records Systems
Papers in
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- Adversarial Robustness in Machine Learning 7
- Anomaly Detection Techniques and Applications 3
- Domain Adaptation and Few-Shot Learning 3
- Natural Language Processing Techniques 2
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- Advanced Neural Network Applications 3
- Multimodal Machine Learning Applications 1
- Co-authors
- J. Zico Kolter (5 shared papers)Frank R. Schmidt (2 shared papers)Jan Hendrik Metzen (1 shared paper)Hadi Salman (2 shared papers)Aleksander Mądry (2 shared papers)Chris Callison-Burch (1 shared paper)Marianna Apidianaki (1 shared paper)Li Zhang (1 shared paper)
- Journals
- Academic Medicine (1 paper)PubMed (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesGermanyIndia
In The Last Decade
Eric Wong
14 papers receiving 215 citations
Eric Wong's Hit Papers
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 169
- Health Information Management 15
- Health Informatics 4
- Hardware and Architecture 15
- Signal Processing 22
Countries citing papers authored by Eric Wong
This map shows the geographic impact of Eric Wong'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 Eric Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Wong more than expected).
Fields of papers citing papers by Eric Wong
This network shows the impact of papers produced by Eric Wong. 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 Eric Wong. The network helps show where Eric Wong may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric Wong, 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 | Scaling provable adversarial defenses | 2018 | 57 |
| 2 | 2023 | 49 | |
| 3 | Jailbreaking Black Box Large Language Models in Twenty Queries Hit paper breakdown → | 2025 | 24 |
| 4 | 2022 | 23 | |
| 5 | 2019 | 22 | |
| 6 | 1994 | 13 | |
| 7 | 2023 | 10 | |
| 8 | Adversarial Robustness Against the Union of Multiple Perturbation Models | 2019 | 8 |
| 9 | 1996 | 7 | |
| 10 | 2022 | 4 | |
| 11 | 2024 | 3 | |
| 12 | Selecting a commercial clinical information system: an academic medical center's experience. | 1994 | 2 |
| 13 | 2015 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2024 | 0 | |
| 16 | 2024 | 0 |
About Eric Wong
Eric Wong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health Information Management, Molecular Biology and General Health Professions, having authored 16 papers that have together received 224 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (7 papers), Anomaly Detection Techniques and Applications (3 papers), Electronic Health Records Systems (3 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Natural Language Processing Techniques (2 papers), Health Sciences Research and Education (2 papers) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Artificial Intelligence (169 citations), Health Information Management (15 citations), Health Informatics (4 citations), Hardware and Architecture (15 citations) and Signal Processing (22 citations). Eric Wong has collaborated with scholars based in United States, Germany and India. Frequent co-authors include J. Zico Kolter, Frank R. Schmidt, Jan Hendrik Metzen, Hadi Salman, Aleksander Mądry, Chris Callison-Burch, Marianna Apidianaki, Li Zhang, Adam Stein and Qing Lyu. Their work appears in journals such as Academic Medicine, PubMed, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), DOAJ (DOAJ: Directory of Open Access Journals) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.