Paul Resnick
Michael D Cohen Collegiate Professor of Information and Professor of Information, School of Information
Tutorial Overview
Explore how generative AI can support a rigorous, advanced approach to pre-registration. This session will demonstrate how researchers can use AI to develop analysis code and create simulated datasets before collecting real-world data—helping them clarify assumptions, test analytical workflows, identify potential problems, and strengthen research transparency and reproducibility.
Reminder: All attendees, please bring a laptop.
About the Series
This tutorial series introduces practical ways researchers can use AI to support common stages of the research workflow. Designed as a hands-on learning experience, the series focuses on approachable, real-world applications rather than abstract theory. Each session will combine brief framing, live demonstrations, and guided practice so participants can explore how AI tools may help with tasks such as refining research questions, working with data, conducting early-stage analysis, checking outputs, and communicating findings responsibly. The goal is to help researchers develop useful habits for integrating AI into their work in thoughtful, transparent, and effective ways.
For questions please message Kelly Psilidis: [email protected]