Devon Hjelm
Impact in
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
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- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
Papers in
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- Functional Brain Connectivity Studies 6
- Neural dynamics and brain function 3
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- Advanced Neuroimaging Techniques and Applications 4
- COVID-19 diagnosis using AI 1
- Co-authors
- Vince D. Calhoun (6 shared papers)Yoshua Bengio (4 shared papers)Sergey Plis (5 shared papers)Aristide Baratin (1 shared paper)Sherjil Ozair (1 shared paper)Mohamed Ishmael Belghazi (1 shared paper)Aaron C. Courville (2 shared papers)Jessica A. Turner (2 shared papers)
- Journals
- NeuroImage (2 papers)Frontiers in Neuroscience (1 paper)Neural Information Processing Systems (1 paper)arXiv (Cornell University) (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Devon Hjelm
11 papers receiving 1.1k citations
Devon Hjelm's Hit Papers
Peers
Comparison fields: 5 of 98
- Cognitive Neuroscience 494
- Radiology, Nuclear Medicine and Imaging 242
- Artificial Intelligence 388
- Health Informatics 16
- Neurology 64
Countries citing papers authored by Devon Hjelm
This map shows the geographic impact of Devon Hjelm'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 Devon Hjelm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Devon Hjelm more than expected).
Fields of papers citing papers by Devon Hjelm
This network shows the impact of papers produced by Devon Hjelm. 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 Devon Hjelm. The network helps show where Devon Hjelm may publish in the future.
Co-authors
The 25 scholars most cited alongside Devon Hjelm, 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 | Deep learning for neuroimaging: a validation study Hit paper breakdown → | 2014 | 457 |
| 2 | Mutual Information Neural Estimation. Hit paper breakdown → | 2018 | 352 |
| 3 | 2014 | 202 | |
| 4 | 2018 | 48 | |
| 5 | 2019 | 8 | |
| 6 | 2017 | 6 | |
| 7 | 2015 | 3 | |
| 8 | 2021 | 3 | |
| 9 | 2025 | 3 | |
| 10 | 2016 | 1 | |
| 11 | GibbsNet: Iterative Adversarial Inference for Deep Graphical Models | 2017 | 1 |
About Devon Hjelm
Devon Hjelm is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Neural dynamics and brain function (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Multimodal Machine Learning Applications (2 papers), Image and Signal Denoising Methods (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Cognitive Neuroscience (494 citations), Radiology, Nuclear Medicine and Imaging (242 citations), Artificial Intelligence (388 citations), Health Informatics (16 citations) and Neurology (64 citations). Devon Hjelm has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Vince D. Calhoun, Yoshua Bengio, Sergey Plis, Aristide Baratin, Sherjil Ozair, Mohamed Ishmael Belghazi, Aaron C. Courville, Jessica A. Turner, Jane S. Paulsen and H. Jeremy Bockholt. Their work appears in journals such as NeuroImage, Frontiers in Neuroscience, Neural Information Processing Systems, arXiv (Cornell University) and International Conference on Machine Learning.
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.