Max Robotics — Global Service Robot Directory + US Certification

About

Christopher Morse is a pioneering researcher at the intersection of underwater robotics, computer vision, and autonomous construction. His primary research areas include semantic segmentation of underwater imagery, human-robot interaction in marine environments, and the automation of design-to-fabrication workflows. Morse’s most impactful contribution is the creation of the SUIM dataset—the first large-scale benchmark for semantic segmentation of underwater imagery, featuring over 1,500 pixel-annotated images across eight object categories including fish, reefs, divers, and robots. This work, with 17 citations, has become a foundational resource for the underwater computer vision community. He has also advanced underwater human-robot interaction through a deep-learned facial recognition system capable of identifying scuba divers even when their faces are heavily obscured by masks and breathing apparatus. In parallel, Morse has explored interactive design, immersive visualization, and automation in construction, and developed a framework for unsupervised inference of relations between sensed object spatial distributions and robot behaviors. His work bridges critical gaps in perception and autonomy for robots operating in complex, unstructured environments, making him a notable figure in field robotics and marine technology.