Rong Zhou

According to our database, Rong Zhou authored at least 22 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation.

Rong Zhou, Houliang Zhou, Yao Su, Brian Y. Chen, Yu Zhang, Lifang He, Alzheimer's Disease Neuroimaging Initiative

CoRR, March, 2026

Diffusion-Guided Pretraining for Brain Graph Foundation Models.

Xinxu Wei, Rong Zhou, Lifang He, Yu Zhang

CoRR, February, 2026

Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models.

Rong Zhou, Dongping Chen, Zihan Jia, Yao Su, Yixin Liu, Yiwen Lu, Dongwei Shi, Yue Huang, Tianyang Xu, Yi Pan, Xinliang Li, Yohannes Abate, Qingyu Chen, Zhengzhong Tu, Yu Yang, Yu Zhang, Qingsong Wen, Gengchen Mai, Sunyang Fu, Jiachen Li, Xuyu Wang, Ziran Wang, Jing Huang, Tianming Liu, Yong Chen, Lichao Sun, Lifang He

CoRR, January, 2026

Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation.

Rong Zhou, Houliang Zhou, Yao Su, Brian Y. Chen, Yu Zhang, Lifang He

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025

Uncovering Alzheimer's Disease Progression via SDE-based Spatio-Temporal Graph Deep Learning on Longitudinal Brain Networks.

Houliang Zhou, Rong Zhou, Yangying Liu, Kanhao Zhao, Li Shen, Brian Y. Chen, Yu Zhang, Lifang He, Alzheimer's Disease Neuroimaging Initiative

CoRR, September, 2025

EfficientLLM: Efficiency in Large Language Models.

Zhengqing Yuan, Weixiang Sun, Yixin Liu, Huichi Zhou, Rong Zhou, Yiyang Li, Zheyuan Zhang, Wei Song, Yue Huang, Haolong Jia, Keerthiram Murugesan, Yu Wang, Lifang He, Jianfeng Gao, Lichao Sun, Yanfang Ye

CoRR, May, 2025

A Survey on Post-training of Large Language Models.

Guiyao Tie, Zeli Zhao, Dingjie Song, Fuyang Wei, Rong Zhou, Yurou Dai, Wen Yin, Zhejian Yang, Jiangyue Yan, Yao Su, Zhenhan Dai, Yifeng Xie, Yihan Cao, Lichao Sun, Pan Zhou, Lifang He, Hechang Chen, Yu Zhang, Qingsong Wen, Tianming Liu, Neil Zhenqiang Gong, Jiliang Tang, Caiming Xiong, Heng Ji, Philip S. Yu, Jianfeng Gao

CoRR, March, 2025

ClusMFL: A Cluster-Enhanced Framework for Modality-Incomplete Multimodal Federated Learning in Brain Imaging Analysis.

Xinpeng Wang, Rong Zhou, Han Xie, Xiaoying Tang, Lifang He, Carl Yang

CoRR, February, 2025

SAMed-2: Selective Memory Enhanced Medical Segment Anything Model.

Zhiling Yan, Sifan Song, Dingjie Song, Yiwei Li, Rong Zhou, Weixiang Sun, Zhennong Chen, Sekeun Kim, Hui Ren, Tianming Liu, Quanzheng Li, Xiang Li, Lifang He, Lichao Sun

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

2024

Normative Modeling for AD Diagnosis and Biomarker Identification.

Songlin Zhao, Rong Zhou, Yu Zhang, Yong Chen, Lifang He

CoRR, 2024

TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation.

Rong Zhou, Zhengqing Yuan, Zhiling Yan, Weixiang Sun, Kai Zhang, Yiwei Li, Yanfang Ye, Xiang Li, Lifang He, Lichao Sun

CoRR, 2024

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos.

Zhiling Yan, Weixiang Sun, Rong Zhou, Zhengqing Yuan, Kai Zhang, Yiwei Li, Tianming Liu, Quanzheng Li, Xiang Li, Lifang He, Lichao Sun

CoRR, 2024

ViT-1.58b: Mobile Vision Transformers in the 1-bit Era.

Zhengqing Yuan, Rong Zhou, Hongyi Wang, Lifang He, Yanfang Ye, Lichao Sun

CoRR, 2024

Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras.

Jun Yu, Yutong Dai, Xiaokang Liu, Jin Huang, Yishan Shen, Ke Zhang, Rong Zhou, Eashan Adhikarla, Wenxuan Ye, Yixin Liu, Zhaoming Kong, Kai Zhang, Yilong Yin, Vinod Namboodiri, Brian D. Davison, Jason H. Moore, Yong Chen

CoRR, 2024

TGNet: tensor-based graph convolutional networks for multimodal brain network analysis.

Zhaoming Kong, Rong Zhou, Xinwei Luo, Songlin Zhao, Ann B. Ragin, Alex D. Leow, Lifang He

BioData Min., 2024

Normative Modeling with Focal Loss and Adversarial Autoencoders for Alzheimer's Disease Diagnosis and Biomarker Identification.

Songlin Zhao, Rong Zhou, Yu Zhang, Yong Chen, Lifang He

Proceedings of the Applications of Medical Artificial Intelligence, 2024

2023

Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V.

Zhiling Yan, Kai Zhang, Rong Zhou, Lifang He, Xiang Li, Lichao Sun

CoRR, 2023

Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics.

Rong Zhou, Houliang Zhou, Brian Y. Chen, Li Shen, Yu Zhang, Lifang He

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease.

Xuetong Wang, Rong Zhou, Kanhao Zhao, Alex D. Leow, Yu Zhang, Lifang He

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics.

Rong Zhou, Houliang Zhou, Li Shen, Brian Y. Chen, Yu Zhang, Lifang He

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease.

Xuetong Wang, Kanhao Zhao, Rong Zhou, Alex D. Leow, Ricardo Osorio, Yu Zhang, Lifang He

CoRR, 2022

2017

The Design and Implementation of Chinese-Uighur-English Online Dictionary Based on Knowledge Graph.

Lirong Qiu, Huan Yang, Rong Zhou

Proceedings of the 2017 IEEE International Conference on Computational Science and Engineering, 2017