About
I am an instructor in Mert Sabuncu's lab at Cornell and Weill Cornell Medicine. I earned my Ph.D. at New York University under guidance of Guido Gerig. My research interest lies in discovering computational techniques and their application to biomedical images.
Recent Updates
April 2024: Thrilled to announce that my NIH K25 career development grant has been awarded! I am excited to explore new opportunities and advance research in prostate cancer.
April 2024: Our review paper on the interpretability of machine learning model for medical imaging (MLMI) led by Alan Wang is published in IEEE Access (Paper).
Oct 2023: Our paper presenting a new method for adjusting for variable confounding associations led by Minh Nguyen was accepted by WACV 2023 (Paper).
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.
Publications
Robust Learning via Conditional Prevalence Adjustment
Pre-print WACV accepted, 2023
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging
MICCAI Workshop MedAGI: Foundation Models for General Medical AI, 2023.
[ Paper ]
The role of AI in prostate MRI quality and interpretation: Opportunities and challenges
European Journal of Radiology, 2023
[ Paper ]
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.
[ Paper | Code | Webpage | Oral presentation |∗Equal contribution ]
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.
[ Paper ]
Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis
MICCAI: Medical Image Computing and Computer Assisted Intervention, 2020.
[ Paper ]
A framework to construct a longitudinal dw-mri infant atlas based on mixed effects modeling of dodf coefficients
MICCAI CDMRI: Computational Diffusion MRI, 2020.
[ Paper | Oral presentation | Best oral presentation award ]
Longitudinal structural connectivity in the developing brain with projective non-negative matrix factorization
SPIE Medical Imaging, 2019.
[ Paper | Oral presentation | Best paper finalist ]
Using individualized brain network for analyzing structural covariance of the cerebral cortex in alzheimer's patients
Frontiers in neuroscience, 2016.
[ Paper ]
Tract-specific correlates of neuropsychological deficits in patients with subcortical vascular cognitive impairment
Journal of Alzheimer's Disease, 2016.
[ Paper ]