DD

Zijian Dong

Ph.D. student

Multimodal Neuroimaging Lab, National University of Singapore

About Me

I am currently a Ph.D. student at the Department of Electrical and Computer Engineering, National University of Singapore (NUS), supervised by Dr. Juan Helen Zhou. Before that, I received B.Eng. degree in Biomedical Engineering from Beihang University (BUAA). I was a visiting undergraduate scholar at Columbia University in the City of New York, supervised by Andrew F. Laine. I have spent some time at United Imaging Intelligence as a research intern, working with Jie-Zhi Cheng.

Interests

NeuroAI
Neuroimaging
Brain Connectivity
Foundation Model
Representation Learning

Education

Ph.D. in Electrical and Computer Engineering
National University of Singapore
B.Eng. in Biomedical Engineering
Beihang University

📚 My Research

My research lies at the intersection of artificial intelligence and neuroimaging, focusing on applications for the diagnosis and prognosis of neurodegenerative diseases. Currently, I am developing a large-scale, multimodal brain foundation model. Additionally, my interests extend to representation learning in broader contexts.

Please reach out to collaborate 😃

Selected Publications

Standardized evaluation of automatic methods for perivascular spaces segmentation in MRI – MICCAI 2024 challenge results. link

Wu Y*, Zhang Y*, Dong Z*, Ji F, Tan AS, Tan G, ..., Wardlaw JM, Valdés Hernández MC, Zhou JH.

Medical Image Analysis (MedIA), 2026.

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure. link

Dong Z*, Lin Y*, Ji F*, Zhou JX, Ng KK, Zhou JH.

European Conference on Computer Vision (ECCV), 2026.

Benchmarking the AI-based diagnostic potential of plasma proteomics for neurodegenerative disease in 17,187 people. link

An L, Pichet-Binette A, Hristovska I, Vilkaite G, Yu X, Zendehdel R, Dong Z, ..., Mattsson-Carlgren N, Hansson O, Vogel JW.

Nature Medicine, 2026 in press.

Joint Adaptation of Uni-modal Foundation Models for Multi-modal Alzheimer's Disease Diagnosis. link

Gu W, Li Y, Jiang X, Wang Z, Li D, Li Z, Dong Z, Zhao C.

International Conference on Learning Representations (ICLR), 2026.

Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens. link

Dong Z*, Li R*, Chong JSX, Dehestani N, Teng Y, Lin Y, Li Z, Zhang Y, Xie Y, Ooi LQR, Yeo BTT, Zhou JH.

Conference on Neural Information Processing Systems (NeurIPS), 2025.

Improve Representation for Imbalanced Regression through Geometric Constraints. link

Dong Z*, Wu Yi*, Chen C*, Zou Y, Zhang Yi, Zhou JH.

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking. link

Dong Z*, Li R*, Wu Yi, Nguyen TT, Chong JSX, Ji F, Tong NRJ, Chen CLH, Zhou JH.

Conference on Neural Information Processing Systems (NeurIPS), 2024 Spotlight (2.08%).

Prompt Your Brain: Scaffold Prompt Tuning for Efficient Adaptation of fMRI Pre-trained Model. link

Dong Z, Wu Y, Chen Z, Zhang Y, Jin Y, Zhou JH.

The International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.

Beyond the Snapshot: Brain Tokenized Graph Transformer for Longitudinal Brain Functional Connectome Embedding. link

Dong Z, Wu Y, Xiao Y, Chong JSX, Jin Y, Zhou JH.

The International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.

COOP-DHGNN: a Framework for Joint Classification and Prediction of Brain Functional Connectivity Using Sparse Trajectory Dataset with Application to Early Dementia. link

Dong Z, Chong JSX, Kok BC, Zhou JH.

IEEE International Conference on Big Data (Big Data), 2022.

(* indicates equal contribution)

Service

Reviewer: CVPR, ICCV, ICML, ICLR, NeurIPS, MICCAI, AISTATS, AAAI, TMI, TMLR, eLife.

Co-organizer: EPVS Segmentation Challenge at MICCAI 2024.

Program committee: NeuroAI Workshop at NeurIPS 2024.