Chenglu Zhu

🧋

祝骋路

Associate Professor (Researcher)

About Me

Chenglu Zhu is an Associate Professor (Researcher) in Artificial Intelligence & Biomedical Image Analysis Lab (Lin Yang’s Lab), School of Engineering, Westlake University. His current research interests include image processing and computer vision, especially the artificial intelligence of medical image analysis.

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Interests

Artificial Intelligence
Computational Vision
BioMedical / Pathology Analysis

Education

PhD Control Science & Engineering
Zhejiang University of Technology
BEng Computer Science & Technology
China jiliang University

📚 My Research

As a research scientist specializing in the intersection of AI and pathology, I am committed to developing robust and efficient diagnostic assistance algorithms that aim to transform the current landscape of pathology.

By integrating fundamental research with clinical practice, my goal is to drive significant breakthroughs in the field, enhancing diagnostic accuracy and patient outcomes.

I am eager to collaborate with fellow researchers and industry experts to advance our understanding and application of AI in pathology, ultimately improving healthcare for all.😃

Featured Publications

Multimodal Large Language Models

PathAsst: Generative Foundation AI Assistant for Pathology

PathAsst is a powerful multimodal AI assistant for pathology, utilizing over 207,000 high-quality image-text pairs and advanced instruction-following techniques to significantly enhance diagnostic and predictive analytics in pathology.

Jan 17, 2024

Carotid Segmentation

Cascaded residual U-net for fully automatic segmentation of 3D carotid artery in high-resolution multi-contrast MR images

We propose a novel fully automatic 3D framework for simultaneous segmentation of the carotid artery from high-resolution multi-contrast MR sequences based on deep learning, achieving superior performance compared to SOAT 3D Unet-based segmentation models.

Feb 11, 2021

Recent Publications

Yuxuan Sun, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Bowen Ding, Tao Lin, Lin Yang (2025). CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic. arXiv.

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Yuxuan Sun, Hao Wu, Chenglu Zhu, Yixuan Si, Qizi Chen, Yunlong Zhang, Kai Zhang, Jingxiong Li, Jiatong Cai, Yuhan Wang, Lin Sun, Tao Lin, Lin Yang (2025). PathBench: Advancing the Benchmark of Large Multimodal Models for Pathology Image Understanding at Patch and Whole Slide Level. IEEE Transactions on Medical Imaging.

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Yuxuan Sun, Yixuan Si, Chenglu Zhu, Xuan Gong, Kai Zhang, Pingyi Chen, Ye Zhang, Zhongyi Shui, Tao Lin, Lin Yang (2025). CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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Honglin Li, Zhongyi Shui, Yunlong Zhang, Chenglu Zhu, Lin Yang (2025). PathVQ: Reforming Computational Pathology Foundation Model for Whole Slide Image Analysis via Vector Quantization. arXiv.

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Yunlong Zhang, Honglin Li, Yunxuan Sun, Sunyi Zheng, Chenglu Zhu, Lin Yang (2025). Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification. Computer Vision – ECCV 2024.

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