Scholar
Xuzhe Zhang
Google Scholar ID: yWuW5UcAAAAJ
PhD Student, Columbia University
Citations & Impact
Citations
333
H-index
8
i10-index
8
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling, accepted at CVPR 2024; PTNet3D: A 3D High-Resolution Longitudinal Infant Brain MRI Synthesizer Based on Transformers, published in IEEE Transactions on Medical Imaging (IEEE-TMI) 2022; recognized as an IEEE TMI Distinguished Reviewer (Gold Level) in 2024; will serve as a reviewer for AISTATS 2025, ICLR 2025, and NeurIPS 2024.
Research Experience
- Served as an AI/ML PhD Intern at GE Healthcare during the 2023 summer, continuing research in advancing medical vision; helped organize the COVID-19 Data Hackathon (Imaging Informatics Section) at IEEE Healthcare Summit 2021.
Education
- Passed the qualifying exam and officially became a Ph.D. candidate (March 2022).
Background
- Interested in studying AI-empowered medical imaging acquisition, processing, and interpretation to transform medical research and clinical practice. Research is multidisciplinary, building on techniques in deep learning, computer vision, and medical imaging. Focused on developing robust vision models for medical image analysis and computing, particularly in generative models, self-/semi-supervised learning, and unsupervised domain adaptation. Recently exploring large vision models and vision language models. On the application side, focused on deploying open-source frameworks in medical/clinical research communities to assist large-scale medical or clinical studies in discovering quantitative image-based markers and thereby improving healthcare.
Miscellany
- Can be reached at xuzhe.z at columbia dot edu. Can also DM him on Twitter.
Co-authors