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About

Craig Jones is pioneering the next generation of image-guided neurosurgery, with a focused mission to overcome the fundamental challenge of brain deformation during deep-brain procedures. His research lies at the intersection of robot-assisted surgery, computer vision, and real-time 3D reconstruction. Jones’s most significant contribution is the development of a vision-based navigation system that uses simultaneous localization and mapping (SLAM) to create real-time 3D reconstructions of the ventricular environment. This work directly addresses the limitations of conventional neuronavigation, which loses accuracy when soft tissues shift during surgery. His landmark 2021 study on robot-assisted ventriculoscopy (11 citations) established the foundational framework for this approach, while his 2023 paper on real-time 3D video reconstruction (9 citations) demonstrated its clinical viability for guiding transventricular neurosurgery. Jones has also applied deep learning to solve critical sub-problems, including data-driven detection of spinal instrumentation and reinforcement learning for autonomous ultrasound probe positioning. His work is particularly impactful for deep-brain stimulation (DBS) procedures, where sub-millimeter electrode placement is essential. By replacing rigid registration with adaptive, vision-based guidance, Jones is laying the groundwork for a new standard of accuracy in minimally invasive neurosurgery.