Patrick M. Pilarski
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces 18
- Motor Control and Adaptation 8
- Human-Computer Interaction top 5%
- Gaze Tracking and Assistive Technology 6
- Rehabilitation top 5%
- Stroke Rehabilitation and Recovery 12
- Biomedical Engineering top 5%
- Muscle activation and electromyography studies 34
- Prosthetics and Rehabilitation Robotics 12
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- Neuroscience and Neural Engineering 22
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- Reinforcement Learning in Robotics 7
- Co-authors
- Richard S. SuttonThomas DegrisJohannes GüntherKlaus DiepoldHao ShenJacqueline S. HebertMichael R. DawsonSophia Adamia
- Journals
- SHILAP Revista de lepidopterología (2 papers)Blood (1 paper)PLoS ONE (5 papers)
- Partner nations
- CanadaUnited StatesGermany
In The Last Decade
Patrick M. Pilarski
73 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 154
- Cognitive Neuroscience 482
- Human-Computer Interaction 111
- Rehabilitation 126
- Biomedical Engineering 789
- Cellular and Molecular Neuroscience 316
Countries citing papers authored by Patrick M. Pilarski
This map shows the geographic impact of Patrick M. Pilarski'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 Patrick M. Pilarski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick M. Pilarski more than expected).
Fields of papers citing papers by Patrick M. Pilarski
This network shows the impact of papers produced by Patrick M. Pilarski. 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 Patrick M. Pilarski. The network helps show where Patrick M. Pilarski may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Patrick M. Pilarski, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 3 | |
| 5 | 2022 | 1 | |
| 6 | 2021 | 8 | |
| 7 | 2020 | 13 | |
| 8 | 2019 | 2 | |
| 9 | General Dynamic Neural Networks for explainable PID parameter tuning in control engineering: An extensive comparison. | 2019 | 0 |
| 10 | 2019 | 31 | |
| 11 | 2018 | 44 | |
| 12 | 2018 | 5 | |
| 13 | 2018 | 30 | |
| 14 | 2015 | 45 | |
| 15 | 2013 | 79 | |
| 16 | Between Instruction and Reward: Human-Prompted Switching. | 2012 | 2 |
| 17 | 2011 | 0 | |
| 18 | 2011 | 123 | |
| 19 | 2010 | 1 | |
| 20 | 2005 | 26 |
About Patrick M. Pilarski
Patrick M. Pilarski is a scholar working on Rehabilitation, Cognitive Neuroscience and Cellular and Molecular Neuroscience, having authored 80 papers that have together received 1.9k indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (34 papers), Neuroscience and Neural Engineering (22 papers), EEG and Brain-Computer Interfaces (18 papers), Stroke Rehabilitation and Recovery (12 papers), Prosthetics and Rehabilitation Robotics (12 papers), Motor Control and Adaptation (8 papers), Reinforcement Learning in Robotics (7 papers) and Gaze Tracking and Assistive Technology (6 papers). The work is most often cited by research in Cognitive Neuroscience (482 citations), Human-Computer Interaction (111 citations) and Rehabilitation (126 citations). Patrick M. Pilarski has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include Richard S. Sutton, Thomas Degris, Johannes Günther, Klaus Diepold, Hao Shen, Jacqueline S. Hebert, Michael R. Dawson, Sophia Adamia, C. Backhouse and Craig S. Chapman. Their work appears in journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.
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.