Cryonics Revival Scenarios and Potential Roadmaps

Person Presentation: Paul Hernandez Herrera

Published in People, Scanners and Imaging.

Paul Hernandez-Herrera is an applied mathematician and postdoctoral fellow who develops algorithms for image analysis at the Institute of Biotechnology, National Autonomous University of Mexico. His prior work includes creating algorithms to automatically identify and trace tubular structures (such as neurons, sperm flagella, and blood vessels) from 3D images. Currently, he is pioneering the use of machine learning and deep learning techniques for automated identification of objects in microscopy images, with particular interest in studying how sperm swim in 3D. This has led us to reassess our most basic ideas surrounding sperm motility, with profound relevance for reproductive science and, potentially, human fertility research. He also develops open source software to ensure his algorithms can be used by the widest audience possible.