Research Overview
We live in an era saturated with supposedly authoritative information — how to be healthy, how to measure success, how we should view history and what AI can and can't do for us. My research asks a simple question: how do we create reliable knowledge when authority and expertise are in flux?
I work across the history of science and medicine, digital humanities, data analytics, and pedagogy — both because I'm generally indecisive, and because these fields illuminate different facets of the same problem. Whether I'm tracing how nineteenth-century dietary advice still shapes what we think of as a "natural" diet , or building open-source tools that challenge the biased metrics universities use to define student success, I'm really nibbling away at epistemological questions that are taking on a new urgency in the era of AI.
Current Projects
Digital Public Humanities
I'm especially interested in how emerging technologies — from interactive archives to immersive storytelling — can bring the past to life in ways that foreground cultural diversity and demonstrate why historical perspective matters now. Through
Amaranth, UNM's digital humanities and public scholarship studio, I work with faculty, students, and community partners to build accessible, public facing projects that showcase their work. I also develop infrastructure for sustainable digital public history projects, including
Xanthan, because too many digital projects die when the grant runs out.
History of Food, Diet, and Health
Americans are buried in conflicting nutritional advice, and most of it comes wrapped in the authority of nutritional science. I study the cultural construction of dietary knowledge in Western medicine, with a current focus on the history of "natural" foods and diets. How did shifting ideas about nature come to define what we consider healthy eating? And what do we lose when we treat historically contingent ideas as true and objective knowledge about what to eat? My food/diet courses — on American food and identity, on the tangled relationship between food / technology /nature, on how dietary experts establish authority — all use food as a lens for examining how cultural values are deeply embedded in everyday food choices.
AI in Higher Education
AI is already reshaping how students learn, how professionals work, and how all of us assess what's trustworthy — often in ways that are hard to see. I'm not interested in whether we should "allow" students to use AI; that ship has sailed. I'm interested in more practical questions: How do we teach students to use AI critically and ethically? How do we help them recognize when it's narrowing their thinking rather than deepening it? And how do we reckon with the way AI is accelerating long-standing questions about authority, expertise, and intellectual labor? These are as much historical as pedagogical questions and my work in the history of knowledge and expertise informs how I approach them.
Higher Ed Success Analytics
Most universities measure student success with the same handful of metrics like retention rates, time to degree, and graduation numbers. These tell you how well students conform to biased, traditional pathways, but they don't tell you much about whether students are actually thriving and what they are getting out of
higher education. With
CEDAR, I'm building a flexible, open-source data analytics platform that helps institutions ask better questions and answer them consistently — the ones that matter to their particular students and contexts — without relying on expensive, one-size-fits-all proprietary tools. The goal isn't just a better dashboard; it's a more honest conversation about what success looks like and how we can collectively assess it.
