Kristina Mach

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About

Kristina Mach is a pioneering researcher at the intersection of ophthalmic surgery and robotics, with a primary focus on advancing subretinal injection techniques for treating vitreoretinal disorders. Her most cited work, "OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach" (2022, 15 citations), addresses the critical challenges of precision and safety in this delicate procedure. Mach’s major contribution lies in integrating deep learning with optical coherence tomography (OCT) imaging to enable real-time, robotic-assisted needle placement—a breakthrough that significantly reduces the risk of retinal damage during therapeutic delivery. By developing robust registration algorithms, she has enhanced the accuracy of robotic systems, making subretinal injections more reliable and accessible for conditions like age-related macular degeneration. Her work bridges computer vision, medical robotics, and clinical ophthalmology, earning recognition for its translational potential. With a growing citation impact, Mach’s research is shaping the future of minimally invasive retinal surgery, offering hope for improved patient outcomes. Her innovative approach continues to inspire students and researchers in biomedical engineering and surgical robotics.