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
Oct 2024: Our team won runner-up in the 2024 MICCAI BraTs Segmentation Challenge (Paper).
Oct 2024: Our paper on generalized prevalence adjustment for distribution shifts, led by Minh Nguyen, was accepted and presented at ECCV 2024. (Paper).
Sep 2024: I was invited to give a talk at the Annual Symposium for Evolving Therapies and Drug Development in Oncology.
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, has been published in IEEE Access (Paper).
Past Updates: See All Updates.
Publications
Effective Segmentation of Post-Treatment Gliomas Using Simple Approaches: Artificial Sequence Generation and Ensemble Models
MICCAI: BraTS Challenge, 2024.
[ Paper | Challenge Runner-Up | ∗Equal contribution ]
Adapting to Shifting Correlations with Unlabeled Data Calibration
ECCV: European Conference on Computer Vision, 2024.
[ Paper ]
Robust Learning via Conditional Prevalence Adjustment
WACV: Winter Conference on Applications of Computer Vision, 2024.
A Framework for Interpretability in Machine Learning for Medical Imaging
IEEE Access, 2024.
[ Paper ]
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 ]