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 these questions through hands-on work in archives and museums, where I focused on building ethical and sustainable digital practices. I contributed to a range of projects, from anti-racist metadata remediation, to digital asset management, and strategic digitization planning for under-resourced institutions. As a TA, I also taught how to utilize Python for social media research data analysis, and guest lectured on algorithmic power, social media, and the politics of digital visibility.

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.