A post-disciplinary research group at the intersection of complex systems, computational social science, and philosophy — part of the Vermont Complex Systems Institute at UVM.
We are a post-disciplinary research group at the Vermont Complex Systems Institute at the University of Vermont.
The lab grew out of a conviction that computational methods and humanistic inquiry need each other. We think the questions that matter most require moving across boundaries: between the formal and the philosophical, the quantitative and the ethical, the technical and the human.
We are rooted in complexity science's tradition of studying systems across scales and how small interactions produce large and often surprising outcomes. We are also rooted in maker and open-source communities that believe knowledge should be built in public, shared freely, and held accountable to the people it affects.
We work on the problems we find both hard and important for society: what stories large language models learn and distort, where individual consent breaks down in networked systems, how human bias shapes the perception of synthetic media. We also try to have fun doing it.
What is actually happening inside models that work with language and what do they do to stories? We study narrative at scale: how stories mutate, how meaning is structured, and what mechanistic interpretability can reveal about the mechanisms behind it.
Individual consent frameworks break down in networked environments, your neighbors' data exposes you whether you opt in or not. We build group-level models for privacy, consent, and data ethics, and extend this thinking to institutional questions such as how should universities, governments, and platforms govern emerging technology at scale?
Our ability to detect deepfakes, misinformation, AI writing bends along context and perception of authenticity is not neutral. We study how bias shapes judgment of synthetic media, what AI-generated work traces back to, and what fairness demands when the line between real and generated dissolves.
Interactive narrative data visualizations — where research surfaces as story. Each piece invites you to scroll deeper into a dataset, a question, a hidden pattern in the dark.
Why do some things go viral while better ones don't? A scrollable investigation into humor, social networks, and the strange mathematics of what spreads.
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How has the American university changed? Mapped through decades of course catalogs and the language institutions use to describe what they think knowledge is.
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Privacy isn't a personality trait — it's a relationship. Across 17 institutional contexts, who you are shapes who you trust: people of color show significantly higher discomfort with police and government, non-binary participants show the largest gaps of any group, and each adverse childhood experience makes institutions of authority feel less safe. One-size-fits-all consent is broken by design.
Coming Soon
Interested in joining? We welcome researchers at all stages who bring curiosity, kindness, rigor, and a commitment to ethics in computational work.
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