Russell H. Taylor

Russell H. Taylor is the John C. Malone Professor in the Department of Computer Science at Johns Hopkins University, with secondary appointments in Mechanical Engineering and the School of Medicine’s Departments of Otolaryngology—Head and Neck Surgery, Radiology and Radiological Science, and Surgery. He is the Lab Director of the Computer Integrated Interventional Systems (CIIS) Laboratory and formerly served as director of the Laboratory for Computational Sensing and Robotics (LCSR), a leading center in medical robotics and autonomous systems. Taylor is a member of the Malone Center for Engineering in Healthcare, the Institute for Assured Autonomy, and the Data Science and AI Institute.

His research spans artificial intelligence, robotics, medical imaging, and human-machine cooperative systems, with a focus on computer-integrated interventional medicine. He pioneered early developments in surgical robotics at IBM, including the Robodoc system and navigation tools for craniofacial surgery. At Johns Hopkins, he led the creation of the NSF-funded Engineering Research Center for Computer-Integrated Surgical Systems and Technology (CISST ERC), advancing foundational technologies in surgical assistance and image-guided therapy.

Taylor is a Fellow of IEEE, AIMBE, MICCAI, and the National Academy of Inventors, and was elected to the National Academy of Engineering in 2020. His accolades include the IEEE Pioneer in Robotics and Automation Award, the MICCAI Enduring Impact Award, and the Honda Prize. He has served as editor-in-chief emeritus of the IEEE Transactions on Robotics and Automation and advised numerous scientific boards.

• BSE, Johns Hopkins University, 1970
• PhD in Computer Science, Stanford University, 1976

Taylor has mentored many students and researchers, contributing to major advancements in medical robotics. His lab collaborates with institutions and industry partners to develop real-time surgical guidance systems, augmented reality tools, and robotic platforms for microsurgery. Future work continues to focus on AI-driven autonomous procedures, digital twins, and enhancing surgeon-robot collaboration.