Publications
62
Citations
356
Est. group size
~2
Recurring co-author estimate
Active years
20
Publishing since 2007
Khalid Youssef develops artificial intelligence and machine learning methods for cardiac medical imaging, particularly cardiovascular magnetic resonance imaging (CMR). Recent work focuses on automated analysis of heart perfusion scans, including detecting reduced blood flow (ischemia), reducing the need for contrast agents and manually labeled training data, and improving MRI image reconstruction. Earlier projects span a broader range of technical topics such as radio-frequency signal classification, biomedical tissue measurement, and landslide prediction.
Publication activity has grown sharply in recent years, rising from one or two papers annually to double digits since 2024.
Generated by claude-opus-4-8 from public bibliographic data · Jul 9, 2026
Typically publishes in teams of ~6 · 0% small-team papers (≤3 authors) · across 8 venues
- Leveraging a CMR Foundation Model for Automated Classification of Stress Perfusion CMR Datasets: Initial Results Using the SCMR Registry
Journal of Cardiovascular Magnetic Resonance · 2026
- Adapting a CMR foundation model for A.I.-powered analysis of perfusion CMR: Enabling 12-fold reduction in manually labeled training dataset for automatic segmentation
Journal of Cardiovascular Magnetic Resonance · 2026
- Quantifying the Impact of Dataset Shifts in Deep Learning-based Dynamic MRI Reconstruction: Need for Spatially Localized Performance Metrics
Journal of Cardiovascular Magnetic Resonance · 2026
- Multi-Stage Deep Learning Enables Accurate Detection of Ischemia in Myocardial Perfusion MRI with Order-of-magnitude Lower Contrast Dose
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025
- Landslide susceptibility modeling by interpretable neural network
Communications Earth & Environment · 2023
- Scalable Undersized Dataset RF Classification: Using convolutional multistage training
IEEE Antennas and Propagation Magazine · 2022
- Mapping Cell Viability Quantitatively and Independently From Cell Density in 3D Gels Noninvasively
IEEE Transactions on Biomedical Engineering · 2021
- Scalable End-to-End RF Classification: A Case Study on Undersized Dataset Regularization by Convolutional-MST
arXiv (Cornell University) · 2021
- Explainable AI Landslide Susceptibility Modeling by Superposable Neural Networks
AGU Fall Meeting Abstracts · 2019
- Machine Learning Approach to RF Transmitter Identification
IEEE Journal of Radio Frequency Identification · 2018
- Noninvasive Quantification of Cell Density in Three-Dimensional Gels by MRI
IEEE Transactions on Biomedical Engineering · 2018
- Machine Learning Approach to RF Transmitter Identification
arXiv (Cornell University) · 2017
- 4-D Flow Control in Porous Scaffolds: Toward a Next Generation of Bioreactors
IEEE Transactions on Biomedical Engineering · 2016
- 16-bit RISC Cryptographic Processor Architecture for Security Operations on Virtex5 FPGA
2016
- Journal of Cardiovascular Magnetic Resonance×17
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition×7
- arXiv (Cornell University)×4
- IEEE Transactions on Biomedical Engineering×3
- Radiology Cardiothoracic Imaging×2
- Behzad Sharif
Medicine · Indiana University
- Thomas J. Brady
Medicine · Purdue University West Lafayette
- Rohan Dharmakumar
Medicine · Indiana University
- Subha V. Raman
Medicine · Indiana University
- Nikita Nair
Medicine · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 27, 2026.
Claim or correct this profile