Max Robotics — Global Service Robot Directory + US Certification

About

Johanna M. Brandenburg is a leading researcher at the intersection of surgical data science and artificial intelligence, with a primary focus on advancing intraoperative situation recognition and machine learning for minimally invasive surgery. Her major contributions center on developing interoperable systems that model, execute, and control complex surgical workflows, addressing the critical challenge of variability in non-standardized procedures. In her highly cited 2023 work, she pioneered the concept of "Surgomics," using active learning to extract surgomic features from robot-assisted minimally invasive esophagectomy—a prospective annotation study that has garnered 16 citations for its innovative approach to personalized surgical outcome prediction. Brandenburg's research bridges the gap between clinical practice and computational modeling, notably demonstrating how standards like BPMN and CMMN can be adapted for dynamic intraoperative processes, a contribution cited 8 times for its potential to create more flexible surgical AI systems. Her work is instrumental in enabling real-time, data-driven decision support during surgery, positioning her as a key figure in the emerging field of surgical process modeling and AI-assisted intervention.