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    <meta name="description" content="Mission, vision, and research philosophy of the Computational Pathology Lab, with focus on reproducible vascular image analysis, spatial biology, and translational pathology.">
    <title>About Us | Computational Pathology Lab</title>
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      <a class="brand" href="index.html"><img src="assets/images/logo/logo.svg" alt="" aria-hidden="true"><span>Computational Pathology Lab</span></a>
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        <p class="eyebrow">About us</p>
        <h1>Computational methods for vascular and spatial pathology</h1>
        <p>The lab brings together pathology, bioinformatics, image analysis, and computational biology to develop reproducible methods for studying cancer tissue, vascular remodeling, and therapy delivery.</p>
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            <p class="eyebrow">Mission</p>
            <h2>Reliable tissue analytics for research discovery</h2>
            <p>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.</p>
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            <p class="eyebrow">Vision</p>
            <h2>Open, interpretable, translational</h2>
            <p>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.</p>
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          <p class="eyebrow">Research philosophy</p>
          <h2>Reproducibility is part of the science</h2>
          <p>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.</p>
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          <article class="card"><h3>Vessel-centered pathology</h3><p>VeSpA-inspired workflows quantify vessel morphology, spatial organization, and vascular remodeling in histological images.</p></article>
          <article class="card"><h3>Spatial and multiplex biology</h3><p>The lab studies cells and tissue structures in context, including vascular organization, immune neighborhoods, and tumor microenvironment patterns.</p></article>
          <article class="card"><h3>Open science</h3><p>Where possible, methods are shared through public repositories, reusable pipelines, and readable documentation.</p></article>
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          <p class="eyebrow">Collaboration</p>
          <h2>Interdisciplinary by design</h2>
          <p>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.</p>
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    <footer class="site-footer"><div class="footer-grid"><div><strong>Computational Pathology Lab</strong><p>Open, reproducible computational pathology research.</p></div><div class="footer-links"><a href="https://github.com/ComputationalPathologyLab">GitHub</a><a href="contact.html">Contact</a></div></div></footer>
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