Ajil Jalal
Impact in
- Acoustics and Ultrasonics top 10%
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- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
Papers in
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- Sparse and Compressive Sensing Techniques 5
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- Image and Signal Denoising Methods 3
- Co-authors
- Alexandros G. Dimakis (6 shared papers)Rebecca Willett (1 shared paper)Greg Ongie (1 shared paper)Richard G. Baraniuk (1 shared paper)Christopher A. Metzler (1 shared paper)Eric Price (4 shared papers)Ashish Bora (1 shared paper)Jonathan I. Tamir (3 shared papers)
- Journals
- Magnetic Resonance in Medicine (1 paper)IEEE Journal on Selected Areas in Information Theory (1 paper)Online Journal of Public Health Informatics (1 paper)DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (1 paper)arXiv (Cornell University) (5 papers)
- Partner nations
- United StatesIndia
In The Last Decade
Ajil Jalal
13 papers receiving 445 citations
Ajil Jalal's Hit Papers
Peers
Comparison fields: 5 of 67
- Acoustics and Ultrasonics 13
- Computer Vision and Pattern Recognition 157
- Computational Mechanics 150
- Radiology, Nuclear Medicine and Imaging 96
- Structural Biology 6
Countries citing papers authored by Ajil Jalal
This map shows the geographic impact of Ajil Jalal'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 Ajil Jalal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajil Jalal more than expected).
Fields of papers citing papers by Ajil Jalal
This network shows the impact of papers produced by Ajil Jalal. 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 Ajil Jalal. The network helps show where Ajil Jalal may publish in the future.
Co-authors
The 14 scholars most cited alongside Ajil Jalal, 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 Techniques for Inverse Problems in Imaging Hit paper breakdown → | 2020 | 332 |
| 2 | 2017 | 93 | |
| 3 | 2023 | 16 | |
| 4 | 2024 | 7 | |
| 5 | 2021 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2015 | 2 | |
| 8 | 2020 | 2 | |
| 9 | 2021 | 2 | |
| 10 | Compressed Sensing with Approximate Priors via Conditional Resampling | 2020 | 2 |
| 11 | 2023 | 2 | |
| 12 | 2016 | 1 | |
| 13 | 2021 | 1 |
About Ajil Jalal
Ajil Jalal is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Signal Processing, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 13 papers that have together received 467 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (5 papers), Image and Signal Denoising Methods (3 papers), Medical Imaging Techniques and Applications (3 papers), Blind Source Separation Techniques (2 papers), Advanced MRI Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Data-Driven Disease Surveillance (1 paper) and Advanced X-ray and CT Imaging (1 paper). The work is most often cited by research in Acoustics and Ultrasonics (13 citations), Computer Vision and Pattern Recognition (157 citations), Computational Mechanics (150 citations), Radiology, Nuclear Medicine and Imaging (96 citations) and Structural Biology (6 citations). Ajil Jalal has collaborated with scholars based in United States and India. Frequent co-authors include Alexandros G. Dimakis, Rebecca Willett, Greg Ongie, Richard G. Baraniuk, Christopher A. Metzler, Eric Price, Ashish Bora, Jonathan I. Tamir, Kannan Ramchandran and Gopala K. Anumanchipalli. Their work appears in journals such as Magnetic Resonance in Medicine, IEEE Journal on Selected Areas in Information Theory, Online Journal of Public Health Informatics, DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) and arXiv (Cornell University).
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.