Osman Mamun obtained his Ph.D. in chemical engineering from the University of South Carolina in 2017, followed by postdoctoral appointments at Stanford University and Pacific Northwest National Laboratory. His experience during his time in academia focused on the applications of machine learning for accelerated materials development, high-throughput screening of materials for targeted applications, and uncertainty quantification and Bayesian optimization for risk assessment of the predictive model. Before joining Enthought, he worked as a machine learning scientist at New Equilibrium Biosciences where he developed a molecular graph machine learning force-field for simulating the drug-protein interactions.
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