Piotr Duda
Impact in
- Artificial Intelligence top 5%
- Data Stream Mining Techniques
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Signal Processing top 5%
- Time Series Analysis and Forecasting
Papers in
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- Data Stream Mining Techniques 20
- Anomaly Detection Techniques and Applications 14
- Machine Learning and Data Classification 5
- Neural Networks and Applications 2
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- Time Series Analysis and Forecasting 8
- Co-authors
- Maciej Jaworski (19 shared papers)Leszek Rutkowski (20 shared papers)Lena Pietruczuk (8 shared papers)Danuta Rutkowska (3 shared papers)Lipo Wang (2 shared papers)Marek Kisiel‐Dorohinicki (2 shared papers)Aleksander Byrski (2 shared papers)Dacheng Tao (2 shared papers)
In The Last Decade
Piotr Duda
23 papers receiving 626 citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 453
- Signal Processing 137
- Management Science and Operations Research 49
- Computer Networks and Communications 87
- Health Information Management 15
Countries citing papers authored by Piotr Duda
This map shows the geographic impact of Piotr Duda'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 Piotr Duda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Piotr Duda more than expected).
Fields of papers citing papers by Piotr Duda
This network shows the impact of papers produced by Piotr Duda. 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 Piotr Duda. The network helps show where Piotr Duda may publish in the future.
Co-authors
The 12 scholars most cited alongside Piotr Duda, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 179 | |
| 2 | 2012 | 87 | |
| 3 | 2013 | 70 | |
| 4 | 2017 | 66 | |
| 5 | 2014 | 54 | |
| 6 | 2016 | 37 | |
| 7 | 2019 | 29 | |
| 8 | 2018 | 23 | |
| 9 | 2017 | 13 | |
| 10 | 2017 | 13 | |
| 11 | 2017 | 13 | |
| 12 | 2019 | 11 | |
| 13 | 2014 | 8 | |
| 14 | 2017 | 6 | |
| 15 | 2016 | 6 | |
| 16 | 2018 | 6 | |
| 17 | 2020 | 5 | |
| 18 | 2023 | 5 | |
| 19 | 2022 | 3 | |
| 20 | 2023 | 3 |
About Piotr Duda
Piotr Duda is a scholar working on Artificial Intelligence, Signal Processing, Control and Systems Engineering, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 644 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (20 papers), Anomaly Detection Techniques and Applications (14 papers), Time Series Analysis and Forecasting (8 papers), Machine Learning and Data Classification (5 papers), Advanced Bandit Algorithms Research (3 papers), Advanced Control Systems Optimization (2 papers), Neural Networks and Applications (2 papers) and Fault Detection and Control Systems (2 papers). The work is most often cited by research in Artificial Intelligence (453 citations), Signal Processing (137 citations), Management Science and Operations Research (49 citations), Computer Networks and Communications (87 citations) and Health Information Management (15 citations). Piotr Duda has collaborated with scholars based in Poland, Singapore and China. Frequent co-authors include Maciej Jaworski, Leszek Rutkowski, Lena Pietruczuk, Danuta Rutkowska, Lipo Wang, Marek Kisiel‐Dorohinicki, Aleksander Byrski, Dacheng Tao, Adam Krzyżak and Jinde Cao. Their work appears in journals such as Information Sciences, Journal of Artificial Intelligence and Soft Computing Research, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and International Journal of Neural 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.