About us
The lab brings together pathology, bioinformatics, image analysis, and computational biology to develop reproducible methods for studying cancer tissue, vascular remodeling, and therapy delivery.
Mission
Our mission is to build computational pathology methods that help researchers extract meaningful, reproducible information from histological and multiplex tissue images. A central focus is robust vessel-feature extraction, including vascular segmentation, morphology, spatial distribution, and links to drug distribution.
Vision
We envision computational pathology as a bridge between morphological expertise and scalable data science. The lab emphasizes methods that are interpretable, reusable, adaptable across imaging contexts, and suitable for interdisciplinary research in oncology, inflammation, fibrosis, and microvascular dysfunction.
Research philosophy
We design workflows so analyses can be inspected, repeated, and adapted. This includes version-controlled code, structured metadata, clear documentation, and practical tools that support collaboration across pathology, bioinformatics, image analysis, and clinical teams.
VeSpA-inspired workflows quantify vessel morphology, spatial organization, and vascular remodeling in histological images.
The lab studies cells and tissue structures in context, including vascular organization, immune neighborhoods, and tumor microenvironment patterns.
Where possible, methods are shared through public repositories, reusable pipelines, and readable documentation.
Collaboration
Computational pathology research depends on sustained collaboration between pathologists, oncologists, biologists, statisticians, computer scientists, and software engineers. The lab welcomes projects where rigorous computational methods can clarify vascular biology, tissue organization, treatment delivery, and translational pathology questions.
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