Robert Stanforth
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Adversarial Robustness in Machine Learning
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
Papers in
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- Adversarial Robustness in Machine Learning 6
- Topic Modeling 4
- Anomaly Detection Techniques and Applications 2
- Internet Traffic Analysis and Secure E-voting 1
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- Physical Unclonable Functions (PUFs) and Hardware Security 2
- Co-authors
- Pushmeet Kohli (8 shared papers)Krishnamurthy Dvijotham (7 shared papers)Sven Gowal (7 shared papers)Po-Sen Huang (3 shared papers)Johannes Welbl (3 shared papers)Dani Yogatama (2 shared papers)Chongli Qin (3 shared papers)Boris Mirkin (2 shared papers)
- Journals
- Nature Medicine (1 paper)Nature (1 paper)SAR and QSAR in environmental research (1 paper)Uncertainty in Artificial Intelligence (1 paper)Studies in classification, data analysis, and knowledge organization (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Robert Stanforth
13 papers receiving 518 citations
Peers
Comparison fields: 5 of 105
- Health Informatics 46
- Artificial Intelligence 353
- Signal Processing 41
- Computer Vision and Pattern Recognition 69
- Computational Theory and Mathematics 53
Countries citing papers authored by Robert Stanforth
This map shows the geographic impact of Robert Stanforth'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 Robert Stanforth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Stanforth more than expected).
Fields of papers citing papers by Robert Stanforth
This network shows the impact of papers produced by Robert Stanforth. 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 Robert Stanforth. The network helps show where Robert Stanforth may publish in the future.
Co-authors
The 22 scholars most cited alongside Robert Stanforth, 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 | 2020 | 91 | |
| 2 | 2019 | 88 | |
| 3 | 2023 | 82 | |
| 4 | 2019 | 81 | |
| 5 | 2024 | 51 | |
| 6 | Adversarial Robustness through Local Linearization | 2019 | 41 |
| 7 | 2007 | 38 | |
| 8 | 2007 | 29 | |
| 9 | Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control | 2020 | 12 |
| 10 | Efficient Neural Network Verification with Exactness Characterization | 2019 | 11 |
| 11 | 2019 | 5 | |
| 12 | Towards Verified Robustness under Text Deletion Interventions | 2020 | 4 |
| 13 | 2007 | 4 |
About Robert Stanforth
Robert Stanforth is a scholar working on Artificial Intelligence, Hardware and Architecture, Computational Theory and Mathematics, Health Informatics and General Social Sciences, having authored 13 papers that have together received 537 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Topic Modeling (4 papers), Anomaly Detection Techniques and Applications (2 papers), Physical Unclonable Functions (PUFs) and Hardware Security (2 papers), Computational Drug Discovery Methods (2 papers), Integrated Circuits and Semiconductor Failure Analysis (2 papers), Internet Traffic Analysis and Secure E-voting (1 paper) and Rough Sets and Fuzzy Logic (1 paper). The work is most often cited by research in Health Informatics (46 citations), Artificial Intelligence (353 citations), Signal Processing (41 citations), Computer Vision and Pattern Recognition (69 citations) and Computational Theory and Mathematics (53 citations). Robert Stanforth has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Pushmeet Kohli, Krishnamurthy Dvijotham, Sven Gowal, Po-Sen Huang, Johannes Welbl, Dani Yogatama, Chongli Qin, Boris Mirkin, Timothy Mann and Jonathan Uesato. Their work appears in journals such as Nature Medicine, Nature, SAR and QSAR in environmental research, Uncertainty in Artificial Intelligence and Studies in classification, data analysis, and knowledge organization.
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.