We developed a model-based software synthesis framework for cyber-physical systems. The framework optimizes the generation of software tasks from functional models and the mapping of those tasks onto embedded platforms, with respect to system safety, performance, security, extensibility, fault tolerance, reliability, memory usage, modularity and reusability. The framework is the first to address timing holistically throughout task generation and task mapping, and enables quantitative trade-offs with emerging design metrics such as security and extensibility.
We developed a cross-layer framework for CPS security that integrates control-theoretic methods at functional layer with cyber-security techniques at embedded platform layer while addressing resource and timing constraints. It provides critical design capability to holistically cope with security and safety challenges in cyber-physical systems. We are exploring the application of this framework in vehicular networks. We have also developed algorithms for applying cyber-security techniques to the currently prevalent CAN (Controller Area Networks) architecture and to the next generation TDMA (time division multiple access) based automotive architecture, while considering resource and timing constraints.
We developed methodologies and algorithms for improving the energy efficiency of buildings, including co-designing HVAC control and embedded platform, co-scheduling heterogeneous energy demands (HVAC, EV charging, datacenter operations) and supplies (grid, renewables, battery), and integrating intelligent building energy management with grid optimization through a proactive demand response framework.
We developed methodologies, algorithms and tools for building real-world vision-based intelligent systems. In particular, We are focusing on developing 1) adaptive visual algorithms that can automatically adapt to the changing physical environment, mission requirements, and resource constraints; 2) better perception algorithms for visual tasks; and 3) system-level design methodologies for building efficient vision-based intelligent systems, in domains such as mobile robots and next-generation connected and autonomous vehicles.