About Me (Google Scholar)
I am a post-doctoral research associate at the Department of Radiology, University of Cambridge, working with Dr Nicholas R. Payne and Prof. Fiona Gilbert. My current research focuses on AI for breast cancer screening. From October 2023 to October 2025, I was a research associate at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, where I worked with Dr Angelica I. Aviles-Rivero and Prof. Carola-Bibiane Schönlieb on machine learning for brain and mental health (particularly interested in the early diagnosis of Alzheimer's Disease). I received my doctor's degree from the University of Surrey, UK, supervised by Prof. Tao Xiang and Prof. Yi-Zhe Song. During my PhD years, I took internships at the University of Cambridge, Shanghai AI Lab, and iFlyTek. I received my master's degree from the University of Chinese Academy of Sciences (UCAS) and Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), supervised by Prof. Yu Qiao and Dr Xiaojiang Peng. I am also fortunate to have worked with Prof. Zhifeng Li from 2016 to 2017.Research Interests
My current research focuses on Artificial Intelligence for healthcare, such as breast cancer screening and the early diagnosis of Alzheimer's Disease.Throughout my research, multimodal learning has been a significant area of concentration. In my postdoctoral work, I aim to apply multimodal foundation models for disease analysis by integrating imaging modalities, such as MRI and PET, with non-imaging data, including genomics and demographics. My PhD thesis addressed distribution shifts across heterogeneous imaging modalities, including sketches, cartoons, and photographs, using domain adaptation techniques. Additionally, my master's thesis focused on face recognition across different imaging modalities, such as near-infrared and visible light images.
A broader research interest includes
- Computer vision and deep learning
- Transfer learning, domain adaptation
- Semi-supervised learning
- Face recognition
- Semantic segmentation
- Medical image analysis
Publications
Please refer to my Google Scholar for the latest and complete publications.Selected papers
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Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis
Zhongying Deng, Haoyu Wang, Ziyan Huang, Lipei Zhang, Angelica I. Aviles-Rivero, Chaoyu Liu, Junjun He, Zoe Kourtzi, Carola-Bibiane Schönlieb. Pattern Recognition, 2025. (Accepted). [ ArXiv version], [Code] -
Generative Model Based Noise Robust Training for Multi-Source Domain Adaptation
Zhongying Deng, Da Li, Junjun He, Xiaojiang Peng, Yi-Zhe Song, Tao Xiang. Pattern Recognition, 2025. (Accepted). -
Bi-Level Optimization-Based Robust Target Training for Multi-Source Domain Adaptation
Zhongying Deng, Da Li, Xiaojiang Peng, Yi-Zhe Song, Tao Xiang. Pattern Recognition, 2025. (Accepted). -
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Zhongying Deng, Yanqi Cheng, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero.
IEEE Transactions on Intelligent Transportation Systems, vol. 26, pp. 2747-2759, 2025. [ ArXiv version], [Data] -
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
Ziyan Huang*, Zhongying Deng*, Haoyu Wang*, Jin Ye*, Yanzhou Su, Tianbin Li, Hui Sun, Junlong Cheng, Jianpin Chen, Junjun He, Yun Gu, Shaoting Zhang, Lixu Gu, Yu Qiao.
Medical Image Analysis, 2025. (* Equal contribution) [Code] -
FCN+: Global Receptive Convolution Makes FCN Great Again
Xiaoyu Ren, Zhongying Deng §, Jin Ye, Junjun He, Yu Qiao, Dongxu Yang, Yi Liu.
NeuroComputing, 2025. (§ Corresponding author) [Code] -
D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction
Lipei Zhang, Rui Sun, Zhongying Deng, Yanqi Cheng, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero.
NeurIPS, 2025. (Accepted). -
SAM-Med3D: A Vision Foundation Model for General-Purpose Segmentation on Volumetric Medical Images
Haoyu Wang, Sizheng Guo, Jin Ye, Zhongying Deng, Junlong Cheng, Tianbin Li, Jianpin Chen, Yanzhou Su, Ziyan Huang, Yiqing Shen, Bin Fu, Shaoting Zhang, Junjun He, Yu Qiao.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025. (Accepted). [Code] -
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica Aviles-Rivero.
International Conference on Machine Learning (ICML), 2024. -
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios
Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, Angelica Aviles-Rivero.
ACM Multimedia, 2024. -
GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI
Pengcheng Chen, Jin Ye, Guoan Wang, Yanjun Li, Zhongying Deng, Wei Li, Tianbin Li, Haodong Duan, Ziyan Huang, Yanzhou Su, Benyou Wang, Shaoting Zhang, Bin Fu, Jianfei Cai, Bohan Zhuang, Eric J Seibel, Junjun He, Yu Qiao.
NeurIPS Datasets and Benchmarks Track, 2024. -
Dynamic Instance Domain Adaptation
Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang
IEEE Transactions on Image Processing (TIP), 2022 [ ArXiv version], [Code] -
Robust Target Training for Multi-Source Domain Adaptation
Zhongying Deng, Da Li, Yi-Zhe Song, Tao Xiang.
The British Machine Vision Conference (BMVC), 2022 (Oral presentation). [Code] -
Domain Attention Consistency for Multi-Source Domain Adaptation
Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang
The British Machine Vision Conference (BMVC), 2021 (Oral presentation) [code] -
Mutual Component Convolutional Neural Networks for Heterogeneous Face Recognition
Zhongying Deng, Xiaojiang Peng, Zhifeng Li, Yu Qiao
IEEE Transactions on Image Processing (TIP), 2019 -
Residual Compensation Networks for Heterogeneous Face Recognition
Zhongying Deng, Xiaojiang Peng, Yu Qiao
AAAI Conference on Artificial Intelligence (AAAI), 2019 [code] -
Adaptive Pyramid Context Network for Semantic Segmentation
Junjun He, Zhongying Deng, Lei Zhou, Yali Wang, Yu Qiao
International Conference on Computer Vision and Pattern Recognition (CVPR), 2019 -
Dynamic Multi-scale Filters for Semantic Segmentation
Junjun He, Zhongying Deng, Yu Qiao
International Conference on Computer Vision (ICCV), 2019 -
Learning Discriminative Representation for Facial Expression Recognition from Uncertainties
Xingyu Fan, Zhongying Deng, Kai Wang, Xiaojiang Peng, Yu Qiao
IEEE International Conference on Image Processing (ICIP), 2020
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Foundation Models for General Medical AI
Won-Ki Jeong, Hyunwoo J. Kim, Zhongying Deng, Yiqing Shen, Angelica I Aviles-Rivero, Shaoting Zhang.
Springer, vol. 16112, ISBN: 978-3-032-07845-2, 2025. -
Foundation Models for General Medical AI
Zhongying Deng, Yiqing Shen, Hyunwoo J. Kim, Won-Ki Jeong, Angelica I Aviles-Rivero, Junjun He, Shaoting Zhang.
Springer, vol. 15184, ISBN: 978-3-031-73470-0, 2024. - Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops: ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023
M. Emre Celebi, Md Sirajus Salekin, Hyunwoo Kim, Shadi Albarqouni, Catarina Barata, Allan Halpern, Philipp Tschandl, Marc Combalia, Yuan Liu, Ghada Zamzmi, Joshua Levy, Huzefa Rangwala, Annika Reinke, Diya Wynn, Bennett Landman, Won-Ki Jeong, Yiqing Shen, Zhongying Deng, Spyridon Bakas, Xiaoxiao Li, Chen Qin, Nicola Rieke, Holger Roth, Daguang Xu.
Springer, vol. 14393, ISBN : 978-3-031-47400-2, 2023
Funding/Grants
- 2024.12 - 2025.12, “Multi-modal Foundation Models for the Early Detection of Neurodegenerative Diseases”. Cambridge Centre for Data-Driven Discovery and Accelerate Program for Scientific Discovery. £22,500.
- 2025.5 - 2025.12, “Vision-Language Foundation Models for the Early Diagnosis of Neurodegenerative Diseases”. Cambridge HPC pioneer project. £5,500 (=10,000 GPU hours * £0.55 per GPU hour).
- 2024.2 - 2025.5, “Machine Learning for Brain and Mental Health”. Cambridge HPC pioneer project. £8,250 (=15,000 GPU hours * £0.55 per GPU hour).
Academic Services
Journal reviewer:- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Image Processing (TIP)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
- International Journal of Computer Vision (IJCV)
- Pattern Recognition
- Neurocomputing
- Transactions on Machine Learning Research (TMLR)
- Artificial Intelligence In Medicine
- International Conference on Computer Vision and Pattern Recognition (CVPR)
- International Conference on Computer Vision (ICCV)
- European Conference on Computer Vision (ECCV)
- AAAI Conference on Artificial Intelligence (AAAI)
- Conference on Neural Information Processing Systems (NeurIPS)
- ACM Multimedia (ACM MM)
- International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
- ICCV 2025 Workshop on GAIA: Generative AI for Biomedical Image Analysis: Opportunities, Challenges and Futures
- MICCAI 2025 3rd International Workshop on Foundation Models for General Medical AI
- MICCAI 2024 2nd International Workshop on Foundation Models for General Medical AI
- MICCAI 2023 1st International Workshop on Foundation Models for General Medical AI
Invited Talks
- 2025, “Hypergraph Learning for Multimodal Brain Disease Analysis”. Cambridge AI cafe (Hosted by CIND, the AI-Brain Hub and the Accelerate Programme), UK
- 2024, “Machine Learning for Brain and Mental Health”. HPC Pioneer Projects Event, Cambridge, UK
- 2024, “NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning”. Society for Industrial and Applied Mathematics (SIAM) Conference on Imaging Science, USA
- 2022, “Dynamic Instance Domain Adaptation”. Cambridge Image Analysis Internal Seminar, UK
- 2022, “Robust Target Training for Multi-Source Domain Adaptation”. BMVC Oral Presentation, UK
- 2021, “Domain Attention Consistency for Multi-Source Domain Adaptation”. BMVC Oral Presentation, UK
- 2019, “Residual Compensation Networks for Heterogeneous Face Recognition”. AAAI Spotlight Presentation, USA