Biography
Veer is pursuing an Engineering DPhil with the Computational Health Informatics (CHI) Lab, where he is supervised by Professor David Clifton.
Veer is passionate about AI-driven innovation in healthcare. He previously completed his BS in Computer Science at Yale University, where he worked with the Cardiovascular Data Science Lab to develop AI-enabled technologies to make the detection of cardiovascular disease more accessible in resource-limited settings across the world. He was awarded a Rhodes Scholarship.
Awards and Prizes
- Rhodes Scholarship
- American Heart Association (AHA) Elizabeth Barrett-Connor Research Award in Epidemiology and Prevention for Investigators in Training, Winner
- Quality of Care Outcomes and Research (QCOR) Early Career Investigator Award, Finalist
Research Interests
Veer's interests include utilizing AI for the analysis of multiple modalities of clinical data from the EHR.
Research Groups
Related Academics
Publications
A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers.
Dhingra LS, Sangha V, Aminorroaya A, Bryde R, Gaballa A et al. (2024)
BibTeX
@misc{amulticentereva-2024/3,
title={A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers.},
author={Dhingra LS, Sangha V, Aminorroaya A, Bryde R, Gaballa A et al.},
year = "2024"
}
Augmenting reality in echocardiography.
Sangha V (2024), Heart (British Cardiac Society), 110(6), 387-388
BibTeX
@article{augmentingreali-2024/2,
title={Augmenting reality in echocardiography.},
author={Sangha V},
journal={Heart (British Cardiac Society)},
volume={110},
pages={387-388},
year = "2024"
}
Biometric contrastive learning for data-efficient deep learning from electrocardiographic images.
Sangha V, Khunte A, Holste G, Mortazavi BJ, Wang Z et al. (2024), Journal of the American Medical Informatics Association : JAMIA, ocae002
BibTeX
@article{biometriccontra-2024/1,
title={Biometric contrastive learning for data-efficient deep learning from electrocardiographic images.},
author={Sangha V, Khunte A, Holste G, Mortazavi BJ, Wang Z et al.},
journal={Journal of the American Medical Informatics Association : JAMIA},
pages={ocae002},
year = "2024"
}
Automated Diagnostic Reports from Images of Electrocardiograms at the Point-of-Care
Khunte A, Sangha V, Oikonomou E, Dhingra LS, Aminorroaya A et al. (2024)
BibTeX
@misc{automateddiagno-2024/,
title={Automated Diagnostic Reports from Images of Electrocardiograms at the Point-of-Care},
author={Khunte A, Sangha V, Oikonomou E, Dhingra LS, Aminorroaya A et al.},
year = "2024"
}
Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images.
Sangha V, Khunte A, Holste G, Mortazavi BJ, Wang Z et al. (2023), medRxiv
BibTeX
@inproceedings{biometriccontra-2023/9,
title={Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images.},
author={Sangha V, Khunte A, Holste G, Mortazavi BJ, Wang Z et al.},
year = "2023"
}
Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images.
Sangha V, Nargesi AA, Dhingra LS, Khunte A, Mortazavi BJ et al. (2023), Circulation, 148(9), 765-777
BibTeX
@article{detectionofleft-2023/8,
title={Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images.},
author={Sangha V, Nargesi AA, Dhingra LS, Khunte A, Mortazavi BJ et al.},
journal={Circulation},
volume={148},
pages={765-777},
year = "2023"
}
Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices.
Khunte A, Sangha V, Oikonomou EK, Dhingra LS, Aminorroaya A et al. (2023), NPJ digital medicine, 6(1), 124
BibTeX
@article{detectionofleft-2023/7,
title={Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices.},
author={Khunte A, Sangha V, Oikonomou EK, Dhingra LS, Aminorroaya A et al.},
journal={NPJ digital medicine},
volume={6},
pages={124},
year = "2023"
}
Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images
Sangha V, Khunte A, Holste G, Mortazavi B, Wang Z et al. (2023)
BibTeX
@misc{biometriccontra-2023/,
title={Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images},
author={Sangha V, Khunte A, Holste G, Mortazavi B, Wang Z et al.},
year = "2023"
}
Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning
Sangha V, Dhingra LS, Oikonomou E, Aminorroaya A, Sikand N et al. (2023)
BibTeX
@misc{identificationo-2023/,
title={Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning},
author={Sangha V, Dhingra LS, Oikonomou E, Aminorroaya A, Sikand N et al.},
year = "2023"
}
Deep Learning-enabled Detection of Aortic Stenosis from Noisy Single Lead Electrocardiograms
Aminorroaya A, Dhingra L, Sangha V, Oikonomou E, Khunte A et al. (2023)
BibTeX
@misc{deeplearningena-2023/,
title={Deep Learning-enabled Detection of Aortic Stenosis from Noisy Single Lead Electrocardiograms},
author={Aminorroaya A, Dhingra L, Sangha V, Oikonomou E, Khunte A et al.},
year = "2023"
}
