River corridor transport & machine learning

At UNM, I work on river corridor transport modeling using community data and physics-aware machine learning.

My contributions

• Unified tracer experiment data across rivers and hydrologic conditions.
• Designed and validated machine learning frameworks in Python.
• Investigated prediction of watershed responses to chemical spills, oil contamination, wildfires, and other disturbances.

Read the solute transport publication