Ziyang Wang

I am a Research Associate at The Alan Turing Institute. Prior to this, I completed my DPhil (PhD) degree in Computer Science at the University of Oxford in 2024, MRes (Master of Research) degree with distinction at Imperial College London in 2018, and BEng (Bachelor of Engineering) degree at Xi’an Jiaotong University in 2017.

Since 2021, I have published over 30 papers as first/corresponding author and 5 papers as co-author [Link] [Link]. The code for all my first-author papers is available on GitHub [Link], with 15 repositories and over 800 stars. I also actively review for over 300 submissions [Link] [Link] for Nature Communications, IEEE TPAMI, IEEE TIP, IEEE TMI, ICLR, ICRA, and IROS, among others. I am a DAAD 2024 AInet Fellow, OYSS 2024 Fellow, received the MICCAI DEMI Best Paper Award, and IEEE SPS Travel Grant.

Feel free to reach out if you'd like to collaborate, share ideas, or simply connect.

Email: ziyang.wang17@gmail.com

Research Interests

Artificial Intelligence, Computer Vision, Data-Centric Engineering, Healthcare AI, Robotics.

Network Architecture: Convolutional Neural Network, Vision Transformer, State Space Model, Kolmogorov-Arnold Networks, Receptance Weighted Key Value.
Network Training: Supervised/Weakly-Supervised/Self-Supervised/Semi-Supervised/Mixed-Supervised/Noise-Robust/Interactive Learning.
Computer Vision for Healthcare: Medical Image Segmentation, Medical Image Registration, Medical Image Inpainting, Object Detection, Depth Estimation, Human Gait Analysis, Person Re-Identification, Surgical Robot Vision.

GitHub Projects

Publications

[First Author]. “DiffKAN-Inpainting: KAN-based Diffusion Model for Brain Tumor Inpainting.” IEEE ISBI. 2025.
[Corresponding-Author]. “Spectral Enhancement and Pseudo-anchor Guidance for Infrared-Visible Person Re-identification.” IEEE ICASSP. 2025.
[Corresponding-Author]. “Uncertainty-Aware Self-attention Model for Time Series Predictive Tasks with Missing Values.” Fractal and Fractional. 2025. [100% APC Discount]
[Co-Author]. “HFE-RWKV: High-Frequency Enhanced RWKV Model for Efficient Left Ventricle Segmentation in Pediatric Echocardiograms.” IEEE ICASSP. 2025.
[Co-Author]. “Zig-RiR: Zigzag RWKV-in-RWKV for Efficient Medical Image Segmentation.” IEEE TMI. 2025.

[First Author]. “Mamba-UNet: UNet-like Pure Visual Mamba for Medical Image Segmentation.” arXiv. 2024. [GitHub 590+ Stars]
[First Author]. “VMambaMorph: a Visual Mamba-based Framework with Cross-Scan Module for Deformable 3D Image Registration.” arXiv. 2024.
[First Author]. “MixSegNet: Fusing Multiple Mixed-Supervisory Signals with Multiple Views of Networks for Mixed-Supervised Medical Image Segmentation.” EAAI. 2024.
[Corresponding-Author]. “GaitFormer: Leveraging Dual-Stream Spatial-Temporal Vision Transformer via a Single Low-Cost RGB Camera for Clinical Gait Analysis.” KBS. 2024.
[Corresponding-Author]. “Semi-Mamba-UNet: Pixel-Level Contrastive and Pixel-Level Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation.” KBS. 2024.
[Corresponding-Author]. “TriConvUNeXt: A Pure CNN-based Lightweight Symmetrical Network for Biomedical Image Segmentation.” Journal of Imaging Informatics in Medicine. 2024.
[Corresponding-Author]. “Quadruple-Consistency Vision Transformer for Medical Image Segmentation with Limited Number of Sparse Annotations.” IEEE ICIP. 2024.
[Co-Author]. “A Survey on Visual Mamba. “ Applied Sciences. 2024.

[First Author]. “Dual-Contrastive Dual-Consistency Dual-Transformer: A Semi-Supervised Approach to Medical Image Segmentation.” ICCV. 2023. [GitHub 110+ Stars]
[First Author]. “Dealing with Unreliable Annotations: A Noise-Robust Network for Semantic Segmentation through A Transformer-Improved Encoder and Convolution Decoder.” Applied Sciences. 2023. [100% APC Discount]
[First Author]. “Exigent Examiner and Mean Teacher: An Advanced 3D CNN-Based Semi-Supervised Brain Tumor Segmentation Framework.” MICCAI-MILLanD. 2023.
[First Author]. “Weakly Supervised Medical Image Segmentation Through Dense Combinations of Dense Pseudo-Labels.” MICCAI-DEMI. 2023. [Best Paper Award]
[First Author]. “Densely Connected Swin-UNet for Multiscale Information Aggregation in Medical Image Segmentation.” IEEE ICIP. 2023.
[Co-Author]. “Residual Aligner-based Network (RAN): Motion-Separable Structure for Coarse-to-fine Discontinuous Deformable Registration.” MedIA, 2023.

[First Author]. “When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation.” ECCV. 2022. [GitHub 110+ Stars]
[First Author]. “Adversarial Vision Transformer for Medical Image Semantic Segmentation with Limited Annotations.” BMVC. 2022.
[First Author]. “Computationally Efficient Vision Transformer for Medical Image Semantic Segmentation via Dual Pseudo-Label Supervision.” IEEE ICIP. 2022. [IEEE Travel Grant]
[First Author]. “Triple-View Feature Learning for Medical Image Segmentation.” MICCAI-REMIA. 2022.
[First Author]. “An Uncertainty-Aware Transformer for MRI Cardiac Semantic Segmentation via Mean Teachers.” MIUA. 2022.

[First Author]. “RAR-U-Net: A Residual Encoder to Attention Decoder by Residual Connections Framework for Spine Segmentation under Noisy Labels.” IEEE ICIP. 2021.
[First Author]. “Quadruple Augmented Pyramid Network for Multi-Class COVID-19 Segmentation via CT.” IEEE EMBC. 2021.
[First Author]. “A Single RGB Camera-Based Gait Analysis with a Mobile Tele-Robot for Healthcare.” IEEE EMBC. 2021.

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