(Active) PI: Scientific machine learning for fluid dynamics surrogate modeling and multiscale data recovery, NERSC AI4Science Compute Allocation, 32,000 A100 GPU Hours and 20,000 CPU Hours on Perlmutter.
(Active) Co-PI: Synthetic Weather Analogs for DoD Exercises, Training, and Simulation, U.S. Air Force SBIR.
(Active) Co-PI: Extending the Analog Ensemble Method for Satellite Observations, U.S. Army STTR.
(Active) Co-PI: Synergistic study of deformation signals and volcano-tectonic earthquakes at Mauna Loa Volcano, HI., National Science Foundation.
(Finished) PI: Margaret-Butler Fellowship project: Scalable machine learning for turbulence closure and reduced-order modeling (2 yr postdoctoral fellowship).
(Finished) PI: SambaWF: Highly resolved surrogate models for weather forecasting, LDRD-Expedition, Argonne National Laboratory, U.S. Department of Energy.
Software development
PythonFOAM, In-situ data analyses with OpenFOAM and Python.
TensorFlowFOAM, A framework that enables the deployment of TensorFlow deep learning models and partial differential equation solutions concurrently in OpenFOAM.
PAR-RL, A framework that leverages the Ray library to deploy scalable deep reinforcement learning for arbitrary scientific environments on leadership class machines.
PyParSVD, A Parallelized, streaming, and randomized implementation of the SVD for Python using mpi4py.
PySPOD, A package to compute the spectral proper orthogonal decomposition in Python.