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Applied AI research for public benefit

AI ethics and applied research

Ethical AI is often discussed as principle and rarely delivered as something a person can actually use. Our work in this program is applied: tools and methods for anyone who needs to judge whether a claim, a citation, or a generated answer can be trusted.

That audience is deliberately broad. Students, journalists, clinicians, librarians, and researchers face the same underlying problem, and it does not take a technical background for it to matter to them.

Library shelves holding reference books Active project

VeritasAudit

A verification tool for citations and sourced claims, built for general use rather than only for academics. AI systems produce references that look correct and are not. VeritasAudit exists to make checking them fast enough that people actually do it.

Read the July 2026 newsletter
Researcher holding a molecular model

Chemistry, engineering, and AI agent systems

Research at the undergraduate and graduate level. Agent systems are increasingly used to plan syntheses, screen candidates, and read literature at scale, which makes their failure modes a chemistry problem as much as a computing one.

Rack of test tubes containing blue solution Chemistry

Experimental and computational

Work emphasizing problems where a result changes practice rather than only the literature.

Researcher pipetting a sample in the lab Chemical engineering

Process and systems

Scaling what works at the bench into something that survives real production constraints.

Equations written on a whiteboard AI agents

Multi-agent architectures

How agent systems coordinate, where they fail, and what verification they need before a lab trusts their output.

Students and collaborators: we take on research partners.

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