Deep learning for atomically resolved imaging techniques: chemical identification and tracking local transformations

Maxim Ziatdinov is a research scientist in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory, where he works at an intersection between physical sciences and advanced data analytics. He is particularly interested in the synergy of theory, experiment, and data analytics for accelerated discoveries in the fields of materials science and nanoscience. This involves development of physics-based data analytics approaches for automatic reading and recognizing complex molecular, atomic and electronic patterns from scanning probe and electron microscopy experiments on various nanoscale systems. Maxim received his PhD in materials science and engineering from Tokyo Institute of Technology in 2014, followed by a postdoctoral appointment at the Center for Nanophase Materials Science in Oak Ridge National Laboratory.