高智凡
个人介绍
姓名： 高智凡
职称： 副教授/博士生导师
电子邮箱： gaozhifan@mail.sysu.edu.cn
联系地址： 广东省深圳市公常路66号中山大学深圳校区医学楼2栋604室
个人主页： http://zhifan-gao.github.io
教育工作经历
2025-至今 国家自然科学基金委员会交叉科学部，流动编制项目主任
2020–至今 中山大学，“百人计划”副教授
2018–2020 加拿大Western University，博士后
2017–2018 中国科学院深圳先进技术研究院，助理研究员/博士后
2014–2017 中国科学院大学，模式识别与智能系统，博士
2005–2011 华中科技大学，电子信息工程，本科/硕士
研究方向
以临床需求为导向，人工智能为核心，计算机视觉为基础，医学图像为应用场景，研究疾病辅助诊断的智能学习基础机制及工程技术。主要包括迁移学习、对抗学习、联邦学习、因果推断、显著性目标检测、目标运动追踪、物理信息模型等。
详细研究方向请看个人主页 http://zhifan-gao.github.io
科研项目（主持）
1. 国家自然科学基金面上项目
2. 国家自然科学基金青年项目
3. 广东省自然科学基金杰出青年项目
4. 广东省自然科学基金面上项目
5. 广东省自然科学基金博士启动项目
6. 中国博士后科学基金面上一等资助
7. 深圳市高等院校稳定资助项目
奖励
1. 吴文俊人工智能科学技术奖优秀青年奖
2. 北京市科学技术进步奖二等奖
3. 广东医学科学技术奖一等奖
4. 中国科学院院长特别奖
5. IOP Trusted Reviewer
6. IEEE TMI Distinguished Reviewer
7. Publons Top Peer Reviewer
学术服务
担任IEEE TPAMI, IEEE TIP, IEEE TMI, IEEE TMM, IEEE TITS, IEEE TII, IEEE JBHI, IEEE SPL, CVPR, ICCV, MICCAI等多个国际期刊和会议的审稿专家。
招聘/招生
副研究员/助理研究员/助理教授/博士后招聘
长期招聘多名医学图像处理方向的副研究员、助理研究员、助理教授和博士后，申请者需具有（或即将拿到）计算机、电子信息、控制、数学、生物医学工程等相关专业背景的博士学位。
硕士研究生招生/实习
欢迎有志于科学研究的保研/考研的同学联系我。我们将一起在人工智能、医学影像分析、计算机视觉方向挖掘新的科学问题，进行新的探索和尝试。同时欢迎在读硕士来实验室实习（本校外校均可）。适合对我的研究方向感兴趣、并准备今后攻读博士学位或出国深造的同学。期待计算机、电子信息、控制、数学、生物医学工程等相关专业背景的同学联系我。
长期招收本科生实习
欢迎本科同学和我一起进行科学研究。我对本科同学的指导是以兴趣+学术为导向，主要培养科研兴趣、学术思维和探索能力。我鼓励本科同学将研究成果发表在学术论文上，或是以参加学术报告的方式对外展示。表现优异者可支持出国参加高水平的学术会议。适合对科研有浓厚兴趣的，或有志于在中山大学继续深造、申请出国攻读硕士/博士学位的同学。期待本科1-3年级，具有一定大学数学和编程基础的同学联系我；也欢迎外校的同学来实验室进行交流。
发表论文
[1] Bi-variational Physics-Informed Operator Network for Fractional Flow Reserve Curve Assessment from Coronary Angiography. B. Xie, H. Zhang, A. Wang, X. Liu, Z. Gao. Medical Image Analysis, 2025.
[2] Bridging Multi-Level Gaps: Bidirectional Reciprocal Cycle Framework for Text-Guided Label-Efficient Segmentation in Echocardiography. Z. Zhang, H. Zhang, T. Zeng, G. Yang, Z. Shi, Z. Gao. Medical Image Analysis, 2025.
[3] Multiple Token Rearrangement Transformer Network with Explicit Superpixel Constraint for Segmentation of Echocardiography. W. Ding, H. Zhang, X. Liu, Z. Zhang, S. Zhuang, Z. Gao, L. Xu. Medical Image Analysis, 2025.
[4] BLENet: a Bio-inspired Lightweight and Efficient Network for Left Ventricle Segmentation in Echocardiography. X. Pang, F. Yao, Y. Zhang, Y. Sun, E. P. L. Lao, C. Lin, P. C. Pang, W. Wang, W. Li, Z. Gao, T. Tan. IEEE Transactions on Circuits and Systems for Video Technology, 2025.
[5] Multi-domain Adversarial Variational Bayesian Inference for Domain Generalization. Z. Gao, S. Guo, C. Xu, J. Zhang, M. Gong, J. D. Ser, S. Li. IEEE Transactions on Circuits and Systems for Video Technology, 2025.
[6] Explainable Classification of Benign-Malignant Pulmonary Nodules With Neural Networks and Information Bottleneck. H. Zhu, W. Liu, Z. Gao, H. Zhang. IEEE Transactions on Neural Networks and Learning Systems, 2025.
[7] Data- and Physics-driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies. J. Huang, Y. Wu, F. Wang, Y. Fang, Y. Nan, C. Alkan, D. Abraham, C. Liao, L. Xu, Z. Gao, W. Wu, L. Zhu, Z. Chen, P. Lally, N. Bangerter, K. Setsompop, Y. Guo, D. Rueckert, G. Wang, G. Yang. IEEE Reviews in Biomedical Engineering, 2025.
[8] Main Coronary Flow Calculation With the Assistance of Physiological Side Branch Flow. A. Wang, H. Zhang, B. Xie, Z. Gao, Y. Dong, C. Peng, X. Liu. IEEE Transactions on Biomedical Engineering, 2025.
[9] Hierarchical Relational Inference for Few-Shot Learning in 3D Left Atrial Segmentation. X. Li, J. Chen, H. Zhang, Y. Cho, S. H. Hwang, Z. Gao, G. Yang. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024.
[10] Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation from Invasive Coronary Imaging. D. Zhang, X. Liu, A. Wang, H. Zhang, G. Yang, H. Zhang, Z. Gao. IEEE Transactions on Medical Imaging, 2024.
[11] Embedding Tasks into the Latent Space: Cross-Space Consistency for Multi-Dimensional Analysis in Echocardiography. Z. Zhang, C. Yu, H. Zhang, Z. Gao. IEEE Transactions on Medical Imaging, 2024.
[12] Collaborative Compensative Transformer Network for Salient Object Detection. J. Chen, H. Zhang, M. Gong, Z. Gao. Pattern Recognition, 2024.
[13] A Deformable Constraint Transport Network for Optimal Aortic Segmentation from CT Images. W. Lin, Z. Gao, H. Liu, H. Zhang. IEEE Transactions on Medical Imaging, 2024.
[14] Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI. Z. Gao, Y. Guo, J. Zhang, T. Zeng, G. Yang, IEEE Transactions on Medical Imaging, 2023.
[15] Progressive Perception Learning for Main Coronary Segmentation in X-ray Angiography. H. Zhang, Z. Gao, D. Zhang, W. K. Hau, H. Zhang. IEEE Transactions on Medical Imaging, 2023.
[16] A Physics-guided Deep Learning Approach for Functional Assessment of Cardiovascular Disease in IoT-based Smart Health. D. Zhang, X. Liu, J. Xia, Z. Gao, H. Zhang, V. H. C. de Albuquerque. IEEE Internet of Things Journal, 2023.
[17] Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images. X. Liu, T. Feng, W. Liu, L. Song, Y. Yuan, W. K. Hau, J. D. Ser, Z. Gao. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023.
[18] Multi-Level Multi-Type Self-Generated Knowledge Fusion for Cardiac Ultrasound Segmentation. X. Liu, T. Feng, W. Liu, L. Song, Y. Yuan, W. K. Hau, J. D. Ser, Z. Gao. Information Fusion, 2023.
[19] Multiple Adversarial Learning based Angiography Reconstruction for Ultra-low-dose Contrast Medium CT. W. Zhang, Z. Zhou, Z. Gao, G. Yang, L. Xu, W. Wu, H. Zhang. IEEE Journal of Biomedical and Health Informatics, 2023.
[20] Intelligent Internet of Things in Mammography Screening using Multicenter Transformation Between Unified Capsules. B. Wang, X. Hu, J. Zhang, C. Xu, Z. Gao. IEEE Internet of Things Journal, 2023.
[21] Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network. Y. Nan, P. Tang, G. Zhang, C. Zeng, Z. Liu, Z. Gao, H. Zhang, G. Yang, IEEE Transactions on Medical Imaging, 2022.
[22] Annealing Genetic GAN for Imbalanced Web Data Learning. J. Hao, C. Wang, G. Yang, Z. Gao, J. Zhang, H. Zhang. IEEE Transactions on Multimedia, 2022.
[23] Multi-Level Semantic Adaptation for Few-Shot Segmentation on Cardiac Image Sequences. S. Guo, L. Xu, C. Feng, H. Xiong, Z. Gao, H. Zhang, Medical Image Analysis, 2021.
[24] Applying Cross-Modality Data Processing for Infarction Learning in Medical Internet of Things. C. Xu, Z. Gao, D. Zhang, J. Zhang, L. Xu, S. Li. IEEE Internet of Things Journal, 2021
[25] Multi-Task Learning for Estimating Multi-Type Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping. C. Yu, Z. Gao, W. Zhang, G. Yang, S. Zhao, H. Zhang, Y. Zhang, S. Li. IEEE Transactions on Neural Networks and Learning Systems, 2021.
[26] Industrial Pervasive Edge Computing-based Intelligence IoT for Surveillance Saliency Detection. J. Zhang, C. Xu, Z. Gao, J. J. P. C. Rodrigues, V. H. C. de Albuquerque. IEEE Transactions on Industrial Informatics, 2021.
[27] Multi-Task Learning for Estimating Multi-Type Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping. C. Yu, Z. Gao, W. Zhang, G. Yang, S. Zhao, H. Zhang, Y. Zhang, S. Li. IEEE Transactions on Neural Networks and Learning Systems, 2020.
[28] Privileged Modality Distillation for Vessel Border Detection in Intracoronary Imaging. Z. Gao, J. Chung, M. Abdelrazek, S. Leung, W. K. Hau, Z. Xian, H. Zhang, S. Li. IEEE Transactions on Medical Imaging, 2020.
[29] Learning Physical Properties in Complex Visual Scenes: An Intelligent Machine for Perceiving Blood Flow Dynamics from Static CT Angiography Imaging. Z. Gao, X. Wang, S. Sun, D. Wu, J. Bai, Y. Yin, X. Liu, H. Zhang, V. H. C. de Albuquerque. Neural Networks, 2020.
[30] Salient Object Detection in the Distributed Cloud-Edge Intelligent Network. Z. Gao, H. Zhang, S. Dong, S. Sun, X. Wang, G. Yang, W. Wu, S. Li, V. H. C. de Albuquerque. IEEE Network, 2020.
[31] Learning the Implicit Strain Reconstruction in Ultrasound Elastography Using Privileged Information. Z. Gao, S. Wu, Z. Liu, J. Luo, H. Zhang, M. Gong, S. Li. Medical Image Analysis, 2019.
[32] Motion Tracking of the Carotid Artery Wall from Ultrasound Image Sequences: a Nonlinear State-Space Approach. Z. Gao, Y. Li, Y.Sun, J. Yang, H. Xiong, H. Zhang, X. Liu, W. Wu, D. Liang, S. Li. IEEE Transactions on Medical Imaging, 2018.
[33] Robust Segmentation of Intima-Media Borders with Different Morphologies and Dynamics During the Cardiac Cycle. S. Zhao, Z. Gao, H. Zhang, Y. Xie, J. Luo, D. Ghista, Z. Wei, X. Bi, H. Xiong, C. Xu, S. Li. IEEE Journal of Biomedical and Health Informatics, 2018.
[34] Robust Estimation of Carotid Artery Wall Motion Using the Elasticity-Based State-Space Approach. Z. Gao, H. Xiong, X. Liu, H. Zhang, D. Ghista, W. Wu, S. Li. Medical Image Analysis, 2017.
[35] Variational Field Constraint Learning for Degree of Coronary Artery Ischemia Assessment. Q. Zhang, X. Liu, H. Zhang, C. Xu, G. Yang, Y. Yuan, T. Tan, Z. Gao. MICCAI, 2024.
[36] Fuzzy Attention-Based Border Rendering Network for Lung Organ Segmentation. S. Zhang, Y. Nan, Y. Fang, S. Wang, X. Xing, Z. Gao, G. Yang. MICCAI, 2024.
[37] Stealing Knowledge from Pre-trained Language Models for Federated Classifier Debiasing. M. Zhu, Q. Yang, Z. Gao, J. Liu, Y. Yuan. MICCAI, 2024.
[38] VertFound: Synergizing Semantic and Spatial Understanding for Fine-Grained Vertebrae Classification via Foundation Models. Y. Wu, J. Tang, Z. Yao, M. Li, Y. Hong, D. Yu, Z. Gao, B. Chen, S. Zhao. MICCAI, 2024.
[39] Conditional Physics-Informed Graph Neural Network for Fractional Flow Reserve Assessment. B. Xie, X. Liu, H. Zhang, C. Xu, T. Zeng, Y. Yuan, G. Yang, Z. Gao. MICCAI, 2023.
[40] Gradient and Feature Conformity-Steered Medical Image Classification with Noisy Labels. X. Xing, Z. Chen, Z. Gao, Y. Yuan. MICCAI, 2023.
[41] A Geometry-Constrainted Deformable Attention Network for Aortic Segmentation. W. Lin, H. Liu, L. Gu, Z. Gao. MICCAI, 2022.
[42] Discrepancy and Gradient-guided Multi-modal Knowledge Distillation for Pathological Glioma Grading. X. Xing, Z. Chen, M. Zhu, Y. Hou, Z. Gao, Y. Yuan. MICCAI, 2022.
[43] CS2: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention. X. Xing, J. Huang, Y. Nan, Y. Wu, C. Wang, Z. Gao, S. Walsh, G. Yang. MICCAI, 2022.
[44] Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI. J. Huang, X. Xing, Z. Gao, G. Yang. MICCAI, 2022.
[45] Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-Branch Multi-scale Attention Network. H. Zhang, D. Zhang, Z. Gao, H. Zhang. MICCAI, 2021.
[46] Context-Aware Inductive Bias Learning for Vessel Border Detection in Multi-modal Intracoronary Imaging. Z. Gao, S. Li. MICCAI, 2019.
[47] Multiview Two-Task Recursive Attention Model for Left Atrium and Atrial Scars Segmentation, J. Chen, G. Yang, Z. Gao, H. Ni, E. Angelini, R. Mohiaddin, T. Wong, Y. Zhang, X. Du, H. Zhang, J. Keegan, D. Firmin. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018.
[48] Direct Detection of Pixel-Level Myocardial Infarction Areas via a Deep-Learning Algorithm. C. Xu, L. Xu, Z. Gao, S. Zhao, H. Zhang, Y. Zhang, X. Du, S. Zhao, D. Ghista, S. Li. MICCAI, 2017.
[49] Carotid Artery Wall Motion Estimated from Ultrasound Imaging Sequences Using a Nonlinear State Space Approach. Z. Gao, Y. Sun, H. Zhang, D. Ghista, Y. Li, H. Xiong, X. Liu, Y. Xie, W. Wu, S. Li. MICCAI, 2016.
[50] Motion Estimation of Common Carotid Artery Wall Using a H∞ Filter Based Block Matching Method. Z. Gao, H. Xiong, H. Zhang, D. Wu, M. Lu, W. Wu, K. K.L. Wong, Y. T. Zhang. MICCAI, 2015.
