Research Overview

My research lies at the intersection of Digital Pathology, Computational Pathology, and Computer Vision. I develop novel AI algorithms and deep learning architectures to address real-world challenges in medical imaging and healthcare.
## Key Research Areas ### 1. Digital Pathology Developing automated systems for analyzing whole-slide histopathological images, including: - Tissue segmentation and cell detection - Stain normalization and image enhancement - Spatial analysis and pattern recognition ### 2. Computational Pathology Creating intelligent diagnostic systems for cancer detection and classification: - Automated tumor detection and classification - Prognostic assessment algorithms - Clinical decision support systems ### 3. Medical Image Analysis Applying machine learning to medical imaging: - Feature extraction and representation learning - Domain adaptation for cross-modality imaging - Multi-modal image fusion and analysis ### 4. Computer Vision & Deep Learning Developing foundational computer vision techniques: - Novel neural network architectures - Self-supervised and weakly-supervised learning - Interpretable AI and explainability ## Join Our Team We are recruiting: - **PhD Students**: Looking for motivated students with interests in medical AI, machine learning, or computer vision - **Postdoctoral Researchers**: Multiple positions available for researchers with strong publication records - **Research Collaborators**: We actively seek collaborations with clinical partners and research institutions **[Contact us →](mailto:jingxin.liu@xjtlu.edu.cn)** | **[Visit VIBE Lab →](https://vibe-lab.example.com)**