(active) Co-PI: AI emulator assisted data assimilation, Future computing, LDRD-Prime, Argonne National Laboratory, U.S. Department of Energy, Amount: $280,000. (PI - Rao Kotamarthi)

(Finished) PI: Margaret-Butler Fellowship project: Scalable machine learning for turbulence closure and reduced-order modeling (2 yr postdoctoral fellowship), Amount: $300,000.

(Finished) PI: SambaWF: Highly resolved surrogate models for weather forecasting, LDRD-Expedition, Argonne National Laboratory, U.S. Department of Energy, Amount: $50,000.

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.