John M. Dolan
Robotics Institute
Carnegie Mellon University
About Professor John M. Dolan
Carnegie Mellon University's Robotics Institute stands as a global beacon for innovation in robotics and artificial intelligence. Renowned for its pioneering contributions, interdisciplinary environment, and academic excellence, the Institute offers an unparalleled ecosystem for advanced research. As a leading institution in autonomous systems, CMU consistently pushes the boundaries of what robotics can achieve, from foundational theoretical work to practical, real-world applications. Its faculty and facilities attract top talent, solidifying its reputation as a premier destination for students and researchers dedicated to shaping the future of robotics.
🧬Research Focus
Within this esteemed environment, Principal Systems Scientist John M. Dolan conducts transformative research at the intersection of autonomous systems, human–robot collaboration, and multi-robot coordination. His work spans critical areas including advanced autonomous driving, emphasizing socially compliant behavior planning, and the development of robust multi-robot systems and telesupervision architectures for large teams. Dolan's expertise in motion planning, robot reliability, and field robotics extends to real-world applications from planetary exploration and harmful algal bloom monitoring to intelligent transportation systems. He focuses on scalable coordination strategies and principled frameworks that balance robot autonomy with human oversight, driving significant advancements in how humans and robots interact effectively in diverse, uncertain environments.
🎓Student Fit & Career
Graduate students eager to contribute to the next generation of robotics will find an exceptional academic mentorship opportunity under Professor Dolan. Ideal PhD students possess strong analytical skills, programming proficiency, and a keen interest in tackling complex, real-world challenges in autonomous systems, human-robot interaction, or multi-robot coordination. Students collaborating on his graduate research projects will develop a deep understanding of complex system design, behavior planning, and field validation techniques. Post-graduation, alumni from his lab are well-prepared for leading careers in robotics R&D within industry, government labs, or academia, shaping the future of intelligent transportation, advanced manufacturing, and exploration technologies.
Research Areas
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