SuperDataScience Ep. 1039: Tulane Professor John Renne on Scaling Urban Research with AI
In Episode #1039, Prof. John Renne (Professor of Real Estate and Urban Planning at Tulane University) joins Jon Krohn to describe what happens when a tenured full professor goes back to school for a master’s in AI. John is a world-leading expert on transit-oriented development who spent decades pushing the limits of Excel and SPSS; learning Python and then vibe coding has let him scale that research by orders of magnitude, from 4,500 American train stations to more than 110,000 worldwide. In this episode, he traces how walkable communities went from academic heresy to the most profitable form of real estate development, explains how computer vision can now put a number on how attractive a street is, describes the undergraduate course he and Jon co-teach at Tulane, and makes the case for AI-led oral exams over AI detectors.
SuperDataScience Podcast released Episode #1039 on October 27, 2026, featuring Prof. John Renne, Professor of Real Estate and Urban Planning at Tulane University. Hosted by Jon Krohn, the episode explores how a tenured full professor returned to academia for a master’s degree in artificial intelligence to transform his long-standing research methods.
Renne, recognized as a leading expert on transit-oriented development, previously relied on Excel and SPSS for data analysis. The show notes indicate that adopting Python and 'vibe coding' allowed him to expand his research scope dramatically, scaling from analyzing 4,500 American train stations to over 110,000 worldwide. This resource offers a practical example of how AI tools can overcome traditional computational limits in social science and urban planning.
Key topics listed in the episode include the evolution of walkable communities into profitable real estate developments, the use of computer vision to quantify street attractiveness, and Renne's argument for AI-led oral exams as a superior alternative to AI detection software. Listeners interested in applying AI to non-tech industries or educational assessment will find these specific use cases relevant.