Over the past decade, cryogenic electron microscopy (cryo-EM) has emerged as a primary method for determining near-native, near-atomic resolution 3D structures of biological macromolecules. Automated approaches to improve throughput and efficiency while lowering costs are needed to meet the increasing demand for cryo-EM. Currently, in the process of collecting high-magnification cryo-EM micrographs, data collection requires human input and manual tuning of parameters, as expert operators must navigate low- and medium-magnification images to find good high-magnification collection locations.