Before entering the GLAM field, I spent a decade running a digital marketing company I co-founded, where I learned firsthand how visibility is manufactured. First, through search engine optimization (SEO), then by proprietary social media platform algorithms. I became concerned about the way algorithmic decision-making was shaping culture, dictating what becomes visible and what remains hidden. This led me to ask deeper questions about access, bias, and the systems we entrust to preserve memory and enable access.

At UCLA, I pursued those questions through hands-on work in archives and museums, focusing on building ethical and sustainable digital practices across collections. I worked on projects ranging from anti-racist metadata remediation to digital asset management system implementation, digitization workflow design, and archival description — across LACMA, the Wende Museum, the Hammer Museum, and the Fowler. I now teach data management and practice as a lecturer in UCLA's MLIS program, where metadata standards, FAIR principles, and the real-world consequences of description decisions are central.

In both marketing and collections work, I encountered the same underlying issue: visibility is not neutral, but constructed. Just as algorithms rank and privilege certain content online, digital collections infrastructures—through metadata, cataloging choices, and system design—determine what rises to the surface and what remains hidden. This recognition has shaped my projects, which often blend hands-on processing with computational analysis and rethinking how digital collections can be explored. At every level, I’m guided by the belief that infrastructure is ethical. The systems we build (how we tag, describe, store, and surface culture) shape what becomes visible, remembered, and valued.