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My guiding principle is "cool heads at the service of warm hearts." I distill challenging material into intuitive, accessible components, building complexity in a logical sequence that supports robust understanding. I bridge theory, empirical evidence, and computation in all courses — working to inspire curiosity, provide intellectual structure, and foster confidence with economic tools.

Echoing Dani Rodrik, the level of abstraction should fit the pedagogical context. In practice, this means beginning with simple concepts and concrete examples before introducing formal machinery, and recognizing that students learn through multiple angles.

Across courses, students consistently highlighted strong preparation, clear explanations, and rigorous, up-to-date content. Common requests centered on pacing, step-by-step coding support (Julia/Python), more in-class examples and interaction, and additional slide detail.

In response, I increased office hours, provided structured Julia materials with Python equivalents, added comprehension checks and short derivation walkthroughs, and expanded opportunities for Q&A. Selected CFQ staff item means ranged from 3.53 to 4.78 across sections.