Nigel Duffy
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Neural Networks and Applications
- Evolutionary Algorithms and Applications
-
- Face and Expression Recognition
Papers in
-
- Machine Learning and Algorithms 4
- Neural Networks and Applications 3
- Machine Learning and Data Classification 2
- Domain Adaptation and Few-Shot Learning 2
-
- Chaos-based Image/Signal Encryption 1
- Co-authors
- Terrence S. Furey (2 shared papers)Michèl Schummer (2 shared papers)David Bednarski (2 shared papers)David Haussler (1 shared paper)Nello Cristianini (2 shared papers)Michael Collins (1 shared paper)David P. Helmbold (4 shared papers)James L. Cole (1 shared paper)
- Journals
- Theoretical Computer Science (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Bioorganic & Medicinal Chemistry Letters (1 paper)Machine Learning (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Nigel Duffy
14 papers receiving 2.2k citations
Nigel Duffy's Hit Papers
Peers
Comparison fields: 5 of 172
- Artificial Intelligence 883
- Computer Vision and Pattern Recognition 350
- Molecular Biology 1.1k
- Analytical Chemistry 89
- Biophysics 49
Countries citing papers authored by Nigel Duffy
This map shows the geographic impact of Nigel Duffy'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 Nigel Duffy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nigel Duffy more than expected).
Fields of papers citing papers by Nigel Duffy
This network shows the impact of papers produced by Nigel Duffy. 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 Nigel Duffy. The network helps show where Nigel Duffy may publish in the future.
Co-authors
The 25 scholars most cited alongside Nigel Duffy, 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 | Support vector machine classification and validation of cancer tissue samples using microarray expression data Hit paper breakdown → | 2000 | 1777 |
| 2 | 2001 | 333 | |
| 3 | 2002 | 121 | |
| 4 | Potential Boosters | 1999 | 27 |
| 5 | 2011 | 18 | |
| 6 | Leveraging for Regression | 2000 | 18 |
| 7 | 2002 | 13 | |
| 8 | 2017 | 5 | |
| 9 | Support Vector Machine | 2004 | 3 |
| 10 | 2020 | 3 | |
| 11 | Document Enhancement System Using Auto-encoders | 2019 | 2 |
| 12 | 2023 | 1 | |
| 13 | 2021 | 1 | |
| 14 | 2002 | 1 |
About Nigel Duffy
Nigel Duffy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Computational Theory and Mathematics, having authored 14 papers that have together received 2.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (4 papers), Neural Networks and Applications (3 papers), Data Quality and Management (2 papers), Machine Learning and Data Classification (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Chaos-based Image/Signal Encryption (1 paper), Web Data Mining and Analysis (1 paper) and Rough Sets and Fuzzy Logic (1 paper). The work is most often cited by research in Artificial Intelligence (883 citations), Computer Vision and Pattern Recognition (350 citations), Molecular Biology (1.1k citations), Analytical Chemistry (89 citations) and Biophysics (49 citations). Nigel Duffy has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Terrence S. Furey, Michèl Schummer, David Bednarski, David Haussler, Nello Cristianini, Michael Collins, David P. Helmbold, James L. Cole, Brian C. Raimundo and Eric H. Anderson. Their work appears in journals such as Theoretical Computer Science, IEEE Transactions on Knowledge and Data Engineering, Bioorganic & Medicinal Chemistry Letters, Machine Learning and Bioinformatics.
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.