Maria Molina
Assistant Professor at NCAR - The National Center for Atmospheric Research
College Park, Maryland, United States
Summary
👤
Senior🎓
Top SchoolMaria Molina is an Assistant Professor at the University of Maryland specializing in data science for climate and extremes, with nine years of research and applied experience spanning academia and national labs. She directs a research group that blends high-resolution modeling and deep learning to study severe convective storms and climate extremes, and maintains active collaborations at NCAR’s Climate and Global Dynamics Laboratory. Her background spans PhD-level earth and ecosystem science, a MA in Climate and Society, and early-career communication roles as a bilingual TV meteorologist, giving her an uncommon mix of public-facing science communication and technical expertise. Maria’s work has bridged operational forecasting, AI-driven lightning and extreme weather challenges, and subseasonal-to-seasonal variability studies, emphasizing actionable insights for risk and preparedness. She holds joint academic appointments and brings a pragmatic, interdisciplinary approach to translating complex climate data into decision-relevant knowledge.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Meteorology, Bachelor of Science - BS, Meteorology at Florida State UniversityMaster of Arts - MA, Climate and Society, Master of Arts - MA, Climate and Society at Columbia University in the City of New YorkDoctor of Philosophy - PhD, Earth and Ecosystem Science, Doctor of Philosophy - PhD, Earth and Ecosystem Science at Central Michigan University
English, Spanish
Stackoverflow
195reputation
21kreached
3answers
2questions
Github Skills (76)
self-organizing-map10
som10
dimensionality-reduction9
ncl9
outlier-detection9
clustering9
prediction9
jupyterlab9
jupyter9
jupyterlab-extension9
unsupervised-learning9
jupyter-widget8
parcel8
eof8
netcdf8
Programming languages (4)
Github contributions (5)
mariajmolina/ML-for-S2S
Jan 2021 - Feb 2023
Repository for subseasonal-to-seasonal prediction and predictability projects using machine learning.
Contributions:21 reviews, 6 PRs, 72 pushes in 2 years 1 month
deep-learningseasonalmachine-learningpredictionsubseasonal
mariajmolina/deep-conus
Sep 2019 - Oct 2022
Contributions:216 commits, 26 pushes in 3 years 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.