Analytics & Integrative Machine Learning (AIML)

CISL's Analytics and Integrative Machine Learning (AIML) group focuses on developing machine learning systems that can effectively integrate within broader Earth System Science observation and prediction frameworks. The group collaborates with the other NCAR labs and university community to produce and evaluate machine learning systems for areas including high impact weather prediction, emulation of Earth system model parameterizations, and analysis of processes driving atmospheric and oceanic phenomena. The group is also actively involved in educating the broader Earth System Science community about machine learning and how it can be applied to their problems. We are organizing an upcoming summer school and have contributed to short courses and hackathons. If you are interested in developing further collaborations, please contact David John Gagne (dgagne@ucar.edu) for more information. 

Group Members:

  • Rich Loft
  • David John Gagne
  • Charlie Becker
  • Gabrielle Gantos
  • Maria Molina
  • Keely Lawrence
  • Gunther Wallach