Daniel Leite
Impact in
- Artificial Intelligence top 2%
- Fuzzy Logic and Control Systems
- Neural Networks and Applications
- Data Stream Mining Techniques
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- Power Systems Fault Detection
- Fault Detection and Control Systems
Papers in
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- Fuzzy Logic and Control Systems 23
- Neural Networks and Applications 17
- Data Stream Mining Techniques 9
- Co-authors
- Fernando Gomide (20 shared papers)Pyramo Costa (16 shared papers)Igor Škrjanc (9 shared papers)Araceli Sanchis (1 shared paper)José Antonio Iglesias (2 shared papers)Edwin Lughofer (1 shared paper)Rosângela Ballini (3 shared papers)Nuno Bettencourt (19 shared papers)
In The Last Decade
Daniel Leite
75 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 711
- Control and Systems Engineering 366
- Cardiology and Cardiovascular Medicine 293
- Management Science and Operations Research 127
- Signal Processing 101
Countries citing papers authored by Daniel Leite
This map shows the geographic impact of Daniel Leite'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 Daniel Leite with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Leite more than expected).
Fields of papers citing papers by Daniel Leite
This network shows the impact of papers produced by Daniel Leite. 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 Daniel Leite. The network helps show where Daniel Leite may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Leite, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 214 | |
| 2 | 2011 | 146 | |
| 3 | 2017 | 108 | |
| 4 | 2012 | 99 | |
| 5 | 2012 | 88 | |
| 6 | 2014 | 76 | |
| 7 | 2017 | 70 | |
| 8 | 2013 | 55 | |
| 9 | 2009 | 50 | |
| 10 | 2020 | 48 | |
| 11 | 2013 | 47 | |
| 12 | 2020 | 47 | |
| 13 | 2019 | 46 | |
| 14 | 2018 | 37 | |
| 15 | 2020 | 37 | |
| 16 | 2019 | 32 | |
| 17 | 2010 | 31 | |
| 18 | 2011 | 25 | |
| 19 | 2011 | 24 | |
| 20 | 2018 | 19 |
About Daniel Leite
Daniel Leite is a scholar working on Artificial Intelligence, Control and Systems Engineering, Cardiology and Cardiovascular Medicine, Electrical and Electronic Engineering and Pulmonary and Respiratory Medicine, having authored 82 papers that have together received 1.6k indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (23 papers), Neural Networks and Applications (17 papers), Data Stream Mining Techniques (9 papers), Cardiac Imaging and Diagnostics (8 papers), Infective Endocarditis Diagnosis and Management (7 papers), Rough Sets and Fuzzy Logic (7 papers), Cardiac Valve Diseases and Treatments (7 papers) and Effects of Environmental Stressors on Livestock (5 papers). The work is most often cited by research in Artificial Intelligence (711 citations), Control and Systems Engineering (366 citations), Cardiology and Cardiovascular Medicine (293 citations), Management Science and Operations Research (127 citations) and Signal Processing (101 citations). Daniel Leite has collaborated with scholars based in Brazil, Portugal and Slovenia. Frequent co-authors include Fernando Gomide, Pyramo Costa, Igor Škrjanc, Araceli Sanchis, José Antonio Iglesias, Edwin Lughofer, Rosângela Ballini, Nuno Bettencourt, Vasco Gama and João Rocha. Their work appears in journals such as Information Sciences, Evolving Systems, IEEE Transactions on Fuzzy Systems, Computers and Electronics in Agriculture and Applied Soft Computing.
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.