About me

I am inspired by scientific efforts that stretch our collective human ability to observe, understand, and improve the world around us. From listening for faint ripples in spacetime (LIGO), to probing the smallest (LHC) and most distant structures (JWST) of the universe. These projects embody a form of inquiry I find deeply inspirational: interdisciplinary, patient, and driven by questions that go beyond any single field. In my own work, I strive to apply that spirit to the brain, developing computational systems that make the brain’s complex, invisible dynamics more visible and measurable.

I am a computational neuroscientist working at the intersection of neuroimaging, digital histopathology, and spatial statistical modeling. My research focuses on understanding how neurodegenerative disease unfolds across the human brain by developing integrative frameworks that unify imaging, pathology, and clinical data within a coherent spatial representation. During my PhD at the University of Washington, advised by Prof. John Gennari and Dr. Paul Crane, I developed NeuroPathPredict (NPP), a spatial modeling framework designed to estimate Alzheimer’s disease–related neuropathology in unsampled brain regions. This work integrates ex vivo MRI, quantitative digital pathology, and machine learning approaches.

Before entering neuroscience, I worked in engineering research and innovation management within industrial R&D environments. That experience shaped how I approach science: as systems-building. I am drawn to problems that require integrating heterogeneous components — data, methods, and people — into scalable, reproducible frameworks that extend beyond a single project or cohort.