Graduate Student, Physics
Paul Hanakata earned his Ph.D. from the department of physics at Boston University in May 2019 and he is currently a postdoctoral fellow in the department of physics at Harvard University. His works include studies of fundamental properties of two-dimensional quantum materials (e.g. graphene) and the development of interpretable deep learning methods. He believes that a physical system is a great playground to test the robustness of modern deep learning as many physical systems are well defined in the sense that the model ground truth does exist. His long term goal is to use deep learning methods to unravel new physics in complex systems that cannot be achieved with the current conventional approach. Currently, he is developing deep learning methods for inverse design in graphene kirigami actuators and connecting deep learning to the renormalization group theory.
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