I'm a computational scientist and scientific ML engineer with 10+ years of experience at the intersection of AI/ML, high-performance computing, and Earth system science 🌎. I specialize in developing, scaling, and optimizing distributed training and inference workflows on multi-node, multi-GPU HPC architectures — with a focus on advancing weather and climate forecasting using deep learning and GPU-accelerated computing.
I currently work as an HPC consultant and computational scientist at the Computational and Information Systems Lab at the National Center for Atmospheric Research, where I support researchers in scaling scientific AI workloads and building GPU-native data pipelines for weather and climate applications. I have a Ph.D. in Chemical Engineering from the University of Iowa, where my thesis focused on performance analysis and optimization of weather and air quality models.
I'm a core open-source contributor to Xarray, CuPy-Xarray, and Project Pythia, and have hands-on experience with domain-specific AI frameworks including NVIDIA PhysicsNeMo, Earth2Studio, ECMWF Anemoi, and NCAR CREDIT.
- 🏔 Boulder, Colorado
- 😄 Pronouns: she/her/hers
📫 Find me on LinkedIn
💬 Ask me about AI/ML for weather and climate, optimizing AI workflows, distributed training on HPC, and scalable geospatial data workflows.
