Name: Ryan Lagerquist
Type: User
Bio: I do machine learning and meteorology. Ph.D. student in Meteorology at U Oklahoma / CIMMS, Google software-engineering intern 2017.
Location: Norman, Oklahoma, USA
Blog: twitter.com/ralager_Wx
Ryan Lagerquist's Projects
Notebooks for AI2ES (NSF Institute for Research on Trustworthy Artificial Intelligence in Weather, Climate, and Coastal Oceanography) short course on XAI (explainable artificial intelligence).
For 2018 Artificial-intelligence and Machine-learning Symposium at University of Oklahoma.
Computes derived fields (e.g., profile-based indices for severe convective weather) from AIWP (AI-based weather prediction) models.
Python library for short course (Machine Learning in Python for Environment) at 2019 AMS (American Meteorological Society) annual meeting.
Same as dopplerchase's CIRA_Diffusion repository, but this one works with Yoonjin's data for the June 13 2024 CIRA tutorial.
Notebooks for CIRA (Cooperative Institute for Research in the Atmosphere) machine-learning short course.
Uncertainty quantification for machine learning at Cooperative Institute for Research in the Atmosphere
Tutorials for CS 5033 (Machine Learning) at University of Oklahoma.
General-exam stuff
End-to-end machine-learning library for predicting thunderstorm hazards.
Contains version-controlled Colab notebook for 2022 paper on loss functions in AMS AIES journal.
Uses machine learning to predict convective initiation and decay from satellite data.
End-to-end library for using machine learning to predict tropical-cyclone intensity.
Machine learning for multi-day prediction of fire weather and behaviour.
Smoke transport modeling / PM2.5 estimation
Interface for humans to label "interesting" (tornado-related) parts of storms and compare their answers with deep learning.
WaveTF: a 1D and 2D wavelet library for TensorFlow and Keras