I am a postdoctoral researcher in Mert Sabuncu's lab at Cornell and Weill Cornell Medicine. I got my Ph.D. at NYU ViDA Research Center, advised by Guido Gerig. My research interest lies in discovering computational techniques and their application to biomedical images.
Oct 2023: I was invited to give a talk at Asilomar Conference on Signals, Systems, and Computers.
Sep 2023: I was invited to give a talk at Annual Symposium for Evolving Therapies and Drug Development in Oncology.
Aug 2023: Our paper showing the application case of UniverSeg for prostate MRI was accepted by MICCAI MedAGI workshop (Paper).
May 2023: I was awarded Postdoctoral Researcher Seed Grant from WCM Radiology.
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Robust Learning via Conditional Prevalence Adjustment
Pre-print WACV accepted, 2023
A Framework for Interpretability in Machine Learning for Medical Imaging
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging
MICCAI Workshop MedAGI: Foundation Models for General Medical AI, 2023.
The role of AI in prostate MRI quality and interpretation: Opportunities and challenges
European Journal of Radiology, 2023
Learning to Compare Longitudinal Images
MIDL: Medical Imaging with Deep Learning, 2023
Pulse Sequence Dependence of a Simple and Interpretable Deep Learning Method for Detection of Clinically Significant Prostate Cancer Using Multiparametric MRI
Academic Radiology, 2022
Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
MICCAI: Medical Image Computing and Computer Assisted Intervention, 2021.
Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
IPMI: Information Processing in Medical Imaging, 2021.
Microparticle-based Biochemical Sensing Using Optical Coherence Tomography and Deep Learning
ACS Nano, 2021.
Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis
MICCAI: Medical Image Computing and Computer Assisted Intervention, 2020.
A framework to construct a longitudinal dw-mri infant atlas based on mixed effects modeling of dodf coefficients
MICCAI CDMRI: Computational Diffusion MRI, 2020.
Longitudinal structural connectivity in the developing brain with projective non-negative matrix factorization
SPIE Medical Imaging, 2019.
Using individualized brain network for analyzing structural covariance of the cerebral cortex in alzheimer's patients
Frontiers in neuroscience, 2016.
Tract-specific correlates of neuropsychological deficits in patients with subcortical vascular cognitive impairment
Journal of Alzheimer's Disease, 2016.