Conducting Research with GenAI: From Ideation to Publication

About

This course trains doctoral students to conduct rigorous, creative, and publishable research in a world where generative AI is an integral part of scientific discovery. Rather than treating GenAI as a writing assistant, students learn to use it as a theoretical and methodological partner across the full research pipeline. The course shows how GenAI fundamentally reshapes theory building, hypothesis generation, literature discovery, measurement design, and data exploration—enabling faster, broader, and more imaginative scientific search while also introducing new risks of conformity, reproducibility, and hallucination. Students are trained in the “New Tools, New Rules” framework (Blanchard et al. 2025), which specifies what parts of the research process should be automated, what must remain human-driven, and how scholars can preserve originality, insight, and contribution when working with AI. Through intensive hands-on research project, students will work in groups to learn how to develop a scalable, journal-ready research program. Students will use GenAI to map literatures, generate and refine theory, design pilot studies, collect and analyze real data, and craft a full research narrative with a forward-looking publication strategy. The emphasis throughout is on producing research that meets the standards of top-tier journals in marketing, psychology, and the behavioral sciences: work that is theoretically grounded, empirically disciplined, and intellectually distinctive—even in an era where AI makes generating ideas and text trivially easy

Course leader

Travis Tae Oh

Target group

Master | PhD | Postdocs | Professionals

Fee info