Ryan K. Cosner

Ryan K. Cosner is an Assistant Professor in the Department of Mechanical Engineering at Tufts University's School of Engineering, commencing his appointment in January 2026. His research bridges robotics, machine learning, and control theory to develop provably safe autonomous systems through risk-aware control frameworks and deployable algorithms validated across diverse robot platforms.

His academic background includes a Ph.D. from the California Institute of Technology (Caltech) and a B.S. from the University of California, Berkeley. Prior to joining Tufts, he contributed to autonomous vehicle research at Nvidia's Autonomous Vehicle Research Group.

Dr. Cosner's work centers onrobotics safety usingControl Barrier Functions (CBFs) to ensure set-invariance under uncertainty. His research spansstochastic safety guarantees,risk-aware control synthesis, andsafe learning frameworks for real-world applications. Key methodologies include discrete-time CBFs, probabilistic safety bounds, and integration of machine learning with formal verification.

Analysis of his 2022-2025 publications reveals dominant themes in safety-critical control for uncertain systems, with significant contributions to humanoid robotics, autonomous vehicles, and stochastic safety frameworks. His work consistently advances CBF theory while addressing practical deployment challenges through validation on physical systems.

No scientific awards were documented in the provided materials.

Dr. Cosner is establishing his research group at Tufts and actively recruiting graduate students for projects in safety-critical autonomy. While specific grants aren't detailed, his research direction aligns with funding priorities in trustworthy AI and robotic systems safety.

He leads a robotics safety laboratory focusing on humanoid platforms and autonomous vehicles, maintaining collaborations with industry partners like Nvidia and academic institutions including Caltech.