About...

The Researcher

With over 13 years of strategic and problem-solving research — and a background in information technology before that — I've spent my career helping organizations untangle complexity to make better decisions.

My doctorate is in Information Science, an interdisciplinary social science that bridges the technical and the human. My professiors trained me to use and adapt a broad range of approaches — user research, contextual inquiry, systems analysis, legal and policy analysis, program evaluation, primary and secondary research, etc. — to solve problems in other domains.

While many research professionals specialize in a particular set of problems, contexts, or tools, I draw from whatever combination of methods the situation calls for — shaped by the people involved, the goals at stake, and the constraints in play. In practice, that's looked like: tracing the gap between what a law intended and how it actually played out; restructuring how biomedical research was classified so the right studies could actually be found; cutting through a crowded AI tool landscape to identify what would genuinely fit a client's workflow; redesigning a process to accelerate the work; or identifying what the evidence actually supported versus what someone assumed it did. No matter the situation, the solution is built for the people who have to live with it.

My doctoral specialization was in natural language processing and computational linguistics. I've worked on projects using machine learning, and I understand how large language models work — which is precisely why I know what AI can't do.

AI is fast. It pattern-matches. It retrieves. But it doesn't see the whole picture — it can miss critical pieces without knowing it. It can't read a room, pick up on what's not being said, or recognize when the answer lies below the surface. It lacks the discernment to navigate ambiguity, the creativity to reframe a problem when the situation demands it, or the judgment to know when something doesn't add up. What I do is acquire working fluency in an unfamiliar domain quickly, use AI and other tools to accelerate that process, and confirm my understanding with experts when needed. Then I synthesize — connecting the dots, accounting for context, and anticipating what the results mean going forward. The outcome isn't just a series of facts; it's a clear, accurate picture of what's actually going on and what it means for the people who need to act on it. That's the work. That's what I do.

What's in a Name?

Noctua Proxima is the practice of Laura Christopherson, PhD. The name Noctua Proxima draws on two Latin roots: noctua, the owl — long a symbol of wisdom and careful observation — and proxima, meaning nearest or closest. Together they express what this practice is meant to be: the wisest resource closest at hand when you need the facts.