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About

Dimitrios Psychogyios is a researcher advancing the frontiers of surgical robotics and computer-assisted intervention. His work centers on two critical, interconnected challenges in minimally invasive surgery: reconstructing the 3D geometry of the surgical site and automatically detecting surgical instruments within the operative field. Psychogyios’s key contribution is demonstrating that these tasks are intrinsically linked and should be solved jointly, rather than in isolation. His most-cited paper, "MSDESIS" (2022, 33 citations), introduces a multitask deep learning framework that simultaneously estimates stereo disparity—for 3D reconstruction—and segments surgical instruments, achieving superior performance by leveraging their shared spatial context. To address the perennial problem of limited annotated surgical data, he developed "SSIS-Seg" (2022, 22 citations), a novel simulation-supervised approach that generates realistic synthetic images for training segmentation models. Psychogyios also played a leading role in the SAR-RARP50 challenge (2023, 11 citations), a benchmark that has become a standard for evaluating tool segmentation and action recognition in robotic prostatectomy. Most recently, he has translated these algorithmic insights into tangible clinical impact, co-developing a handheld robot for endoscopic skull base surgery, with promising preclinical validation (2024). His work is foundational for the next generation of autonomous and semi-autonomous surgical systems.