Aadarsh Padiyath

Aadarsh Padiyath studies how people decide what role generative AI should play in their work and learning. His research introduces the concept of reliance boundaries: the standards people set, test, and revise for what to hand off to AI, what to question, and what to keep doing themselves. Combining qualitative methods like interviews and thematic analysis with surveys, regression, and design-based research, he has traced these boundaries from undergraduate Python classrooms to professional software teams, showing that reliance decisions are shaped less by what AI can do than by the values, peer norms, and social position people bring to it.

Aadarsh has published 16 peer-reviewed papers at venues including ACM CHI, ICER, and SIGCSE TS, earning a CHI Best Paper Honorable Mention and a SIGCSE TS Best Paper Award, with his work cited over 300 times. His classroom tools are used by instructors at UC San Diego, the University of Illinois Chicago, Vanderbilt, and the University of Washington, and are integrated into the Runestone Academy e-textbook platform, reaching over 90,000 students and 4,500 teachers annually. He has also consulted with Gartner Research on GenAI adoption among software engineers and was named a 2025–26 Gary M. Olson Outstanding Ph.D. Student.

Pronouns

he/him

Dissertation title

Critical Consciousness in Computing Education: From Theory to Measurement to Practice

Areas of interest

Human-Centered AI; Computing Ethics; Computing Education

Education

BS in Computer Science, Georgia Institute of Technology, 2019
MS in Computer Science, Georgia Institute of Technology, 2021
PhD in Information, University of Michigan, 2026