Dogan Ulus

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About

Dogan Ulus is a leading researcher at the intersection of formal methods, cyber-physical systems, and robotics. His work primarily focuses on runtime verification and temporal logic monitoring, with a particular emphasis on Metric Temporal Logic (MTL) for specifying and analyzing complex system behaviors. Ulus’s major contributions include developing innovative online monitoring techniques, such as the unified construction of sequential networks for MTL, which enables efficient, real-time analysis of temporal patterns with timing constraints. This work has significant applications in property-based testing, robotics, optimization, and learning for autonomous systems. His highly cited 2018 special session paper on embedded software for robotics surveys critical challenges in designing, implementing, and verifying software for mobile robots, including self-driving cars, addressing programming support, secure state estimation, and ROS-based middleware. With papers accumulating citations that reflect growing influence in the formal methods and robotics communities, Ulus continues to advance the reliability and safety of autonomous systems through rigorous formal verification techniques.