Symbolic Regression for AI-Driven Scientific Discovery
Building AI-for-Science workflows using symbolic regression to support interpretable scientific discovery and experiment analysis.
Duration: Sep. 2025 – Present Advisor: Dr. Yaohang Li, Old Dominion University
This project focuses on developing AI-for-Science workflows that leverage symbolic regression techniques to support interpretable scientific discovery and experiment analysis. The goal is to bridge the gap between data-driven AI methods and human-understandable scientific models.
Keywords: AI for Science, Symbolic Regression, Scientific Computing