SURF Mentoring
Potential projects/topics: One student that will work with satellite images and computer vision models. The student will prepare the training set for a computer vision model to dectect and count how many cactus exists on subsets of satellite images.
Potential skills gained: satellite image processing and computer vision
Required qualifications or skills: Student should know how to code in python, preferably with a computer science background
Direct mentor: Faculty/P.I., Graduate Student
Research Areas
Dr. Noemi Vergopolan is a computational hydrologist on the water and climate nexus. Her research aims to aid actionable decision-making by improving hydrological information for monitoring and forecasting hydrological extremes and their impacts at the local scales. To this end, she develops scalable computational approaches for high-resolution hydrological prediction by leveraging advances in satellite remote sensing, land surface modeling, machine learning, data fusion, and high-performance computing.
