Paula Herber
Papers
5
Total Citations
32
H-Index
3
About
Paula Herber is a leading researcher at the intersection of formal verification, embedded systems, and autonomous hybrid systems. Her work focuses on ensuring the correctness and safety of complex, safety-critical software—from real-time operating systems to intelligent controllers that combine discrete and continuous dynamics with machine learning. Her most cited paper, "Formal Verification of Intelligent Hybrid Systems that are Modeled with Simulink and the Reinforcement Learning Toolbox" (2021, 16 citations), tackles the critical challenge of verifying systems that integrate reinforcement learning, a notoriously opaque component. She has also pioneered reusable formal models for concurrency and communication in custom real-time operating systems (2024, 7 citations), addressing a fundamental need in embedded software design. Her contributions extend to education, where she developed a multi-robot search platform using LEGO Mindstorms (2017) to teach embedded software design. With a strong emphasis on automation and reusability—as seen in her work on specification patterns for resilience verification (2024)—Herber is shaping the future of dependable autonomous systems, making formal methods practical for the next generation of engineers.
Research Focus
Key Achievements
Top Papers
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- 3A multi-robot search using LEGO mindstorms4 citations · 2017
- 4Automated Verification of Embedded Control Software3 citations · 2020
- 5