Mustafa Mustafa is a Machine Learning Engineer at NERSC supercomputing center. His current interests are in deep learning optimization at scale, spatio-temporal generative models for surrogate modeling, generative model training dynamics and application to scientific problems. Mustafa demonstrated GANs abilities to model cosmology convergence maps with very high fidelity (CosmoGAN). Mustafa enjoys communicating science and lecturing on deep learning and how it works. Mustafa’s background is in experimental high energy nuclear physics, he obtained his Ph.D. from Purdue University and postdoc at the Nuclear Science Division at Berkeley Lab.
AI/Machine Learning/Deep Learning