Samuel C. Hoffman
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 1%
- Ethics and Social Impacts of AI
Papers in
-
- Explainable Artificial Intelligence (XAI) 5
- Adversarial Robustness in Machine Learning 3
-
- Computational Drug Discovery Methods 4
- Co-authors
- Prasanna Sattigeri (7 shared papers)Kush R. Varshney (7 shared papers)Aleksandra Mojsilović (7 shared papers)John T. Richards (5 shared papers)Michael Hind (6 shared papers)Stephanie Houde (6 shared papers)Rachel Bellamy (6 shared papers)Vijil Chenthamarakshan (6 shared papers)
- Journals
- IBM Journal of Research and Development (2 papers)Science Advances (1 paper)IEEE Software (1 paper)Nature Machine Intelligence (1 paper)Journal of Machine Learning Research (1 paper)
- Partner nations
- United StatesUkraineIndia
In The Last Decade
Samuel C. Hoffman
14 papers receiving 849 citations
Samuel C. Hoffman's Hit Papers
Peers
Comparison fields: 5 of 117
- Health Informatics 126
- Safety Research 347
- Artificial Intelligence 431
- Computer Science Applications 27
- Computational Theory and Mathematics 63
Countries citing papers authored by Samuel C. Hoffman
This map shows the geographic impact of Samuel C. Hoffman'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 Samuel C. Hoffman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel C. Hoffman more than expected).
Fields of papers citing papers by Samuel C. Hoffman
This network shows the impact of papers produced by Samuel C. Hoffman. 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 Samuel C. Hoffman. The network helps show where Samuel C. Hoffman may publish in the future.
Co-authors
The 25 scholars most cited alongside Samuel C. Hoffman, 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 | AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias Hit paper breakdown → | 2019 | 510 |
| 2 | 2019 | 88 | |
| 3 | AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models | 2020 | 41 |
| 4 | Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance Hit paper breakdown → | 2025 | 41 |
| 5 | 2021 | 38 | |
| 6 | 2020 | 37 | |
| 7 | CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models | 2020 | 33 |
| 8 | 2023 | 30 | |
| 9 | 2020 | 22 | |
| 10 | 2019 | 22 | |
| 11 | 2022 | 11 | |
| 12 | 1995 | 5 | |
| 13 | 2022 | 4 | |
| 14 | 2025 | 4 | |
| 15 | Application of Active Instability Control to a Heavy Duty Gas Turbine | 1999 | 1 |
About Samuel C. Hoffman
Samuel C. Hoffman is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Health Informatics and Safety Research, having authored 15 papers that have together received 887 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (5 papers), Computational Drug Discovery Methods (4 papers), Adversarial Robustness in Machine Learning (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Protein Structure and Dynamics (2 papers), vaccines and immunoinformatics approaches (2 papers), Machine Learning in Materials Science (2 papers) and Ethics and Social Impacts of AI (2 papers). The work is most often cited by research in Health Informatics (126 citations), Safety Research (347 citations), Artificial Intelligence (431 citations), Computer Science Applications (27 citations) and Computational Theory and Mathematics (63 citations). Samuel C. Hoffman has collaborated with scholars based in United States, Ukraine and India. Frequent co-authors include Prasanna Sattigeri, Kush R. Varshney, Aleksandra Mojsilović, John T. Richards, Michael Hind, Stephanie Houde, Rachel Bellamy, Vijil Chenthamarakshan, Kalapriya Kannan and Sameep Mehta. Their work appears in journals such as IBM Journal of Research and Development, Science Advances, IEEE Software, Nature Machine Intelligence and Journal of Machine Learning Research.
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.