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About

Oleg Sokolsky is a prominent researcher whose work spans hybrid systems modeling, embedded software generation, runtime verification, and cyber-physical systems security. His career has been defined by a commitment to bridging the gap between high-level formal models and real-world deployable systems, particularly in safety-critical embedded and autonomous contexts. Sokolsky's most influential contributions center on the automatic generation of embedded software from hierarchical hybrid models, a line of work that has accumulated nearly 80 citations across related publications and established rigorous correspondences between formal models and executable code. His integrated framework for model-based testing and monitoring of hybrid embedded systems (47 citations) further cemented his role in advancing verification methodologies for complex, mixed continuous-discrete systems. Notably, his 2014 work on attack-resilient state estimation for autonomous robots (57 citations) extended his expertise into cybersecurity, addressing malicious sensor and actuator attacks threatening robotic safety. Sokolsky has also contributed the CHARON and R-Charon modeling languages for reconfigurable hybrid systems, explored runtime monitoring through SMEDL, and more recently tackled resilience in cyber-physical systems through checkpointing and recovery frameworks. His body of work reflects a sustained effort to make safety-critical systems both formally rigorous and practically deployable.