Lukas Ruff
Impact in
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Explainable Artificial Intelligence (XAI)
- AI in cancer detection
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
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- AI in cancer detection 9
- Anomaly Detection Techniques and Applications 4
- Explainable Artificial Intelligence (XAI) 4
- Domain Adaptation and Few-Shot Learning 1
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- Artificial Intelligence in Healthcare and Education 1
- Co-authors
- Robert A. Vandermeulen (4 shared papers)Marius Kloft (4 shared papers)Lucas Deecke (3 shared papers)Alexander Binder (1 shared paper)Shoaib Ahmed Siddiqui (1 shared paper)Emmanuel Müller (1 shared paper)Nico Görnitz (1 shared paper)Stephan Mandt (1 shared paper)
- Journals
- Nature Communications (2 papers)European Journal of Cancer (2 papers)Annual Review of Pathology Mechanisms of Disease (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Cell Systems (1 paper)
- Partner nations
- GermanySouth KoreaUnited States
In The Last Decade
Lukas Ruff
14 papers receiving 932 citations
Lukas Ruff's Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 642
- Health Informatics 28
- Industrial and Manufacturing Engineering 87
- Computer Vision and Pattern Recognition 79
- Computer Networks and Communications 54
Countries citing papers authored by Lukas Ruff
This map shows the geographic impact of Lukas Ruff'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 Lukas Ruff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lukas Ruff more than expected).
Fields of papers citing papers by Lukas Ruff
This network shows the impact of papers produced by Lukas Ruff. 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 Lukas Ruff. The network helps show where Lukas Ruff may publish in the future.
Co-authors
The 25 scholars most cited alongside Lukas Ruff, 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 | Deep One-Class Classification Hit paper breakdown → | 2018 | 572 |
| 2 | 2019 | 142 | |
| 3 | 2023 | 91 | |
| 4 | 2022 | 58 | |
| 5 | 2019 | 39 | |
| 6 | 2025 | 14 | |
| 7 | 2025 | 10 | |
| 8 | 2024 | 9 | |
| 9 | 2023 | 6 | |
| 10 | 2024 | 6 | |
| 11 | Transfer-Based Semantic Anomaly Detection | 2021 | 5 |
| 12 | 2025 | 3 | |
| 13 | 2026 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2023 | 0 | |
| 16 | 2024 | 0 | |
| 17 | 2026 | 0 | |
| 18 | 2026 | 0 |
About Lukas Ruff
Lukas Ruff is a scholar working on Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging, Oncology and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 958 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Anomaly Detection Techniques and Applications (4 papers), Explainable Artificial Intelligence (XAI) (4 papers), Single-cell and spatial transcriptomics (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Artificial Intelligence in Healthcare and Education (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Lung Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Artificial Intelligence (642 citations), Health Informatics (28 citations), Industrial and Manufacturing Engineering (87 citations), Computer Vision and Pattern Recognition (79 citations) and Computer Networks and Communications (54 citations). Lukas Ruff has collaborated with scholars based in Germany, South Korea and United States. Frequent co-authors include Robert A. Vandermeulen, Marius Kloft, Lucas Deecke, Alexander Binder, Shoaib Ahmed Siddiqui, Emmanuel Müller, Nico Görnitz, Stephan Mandt, Klaus- Robert Müller and Grégoire Montavon. Their work appears in journals such as Nature Communications, European Journal of Cancer, Annual Review of Pathology Mechanisms of Disease, IEEE Transactions on Neural Networks and Learning Systems and Cell Systems.
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.