The goal of iCyPhy (pronounced eye-sigh-fie) is to conduct pre-competitive research on architectures and design, modeling, and analysis techniques for cyber-physical systems, with emphasis on industrial applications. Cyber-physical systems integrate computing, networking, and physical components. Applications include transportation systems, automation, security, smart buildings, smart cities, medical systems, energy generation and distribution, water distribution, agriculture, process control, asset management, and robotics.
The CPS intellectual challenge is about the intersection, not the union, of the physical and the cyber. This intersection combines engineering models and methods from mechanical, environmental, civil, electrical, biomedical, chemical, aeronautical and industrial engineering with the models and methods of computer science and engineering. iCyPhy research is founded on the conviction that these models and methods do not combine easily, and that consequently CPS constitutes a new engineering discipline that demands its own models and methods.
Research Focus under Edward Lee:
- Model-based design of cyber-physical systems.
- Highly dynamic networked systems (lifetime management, connectivity, adaptation).
- The Internet of things (IoT), swarm systems, edge computing, and smart gateways.
- Safety, privacy, and security for IoT.
- Synthesis and learning for cyber-physical system design and adaptation.
- Localization and location-aware services.
- Software and network architectures for heterogeneous distributed IoT applications.
- Integration of learning and optimization into safety-critical systems.
- Human-in-the-loop systems.
- Systems-of-systems design.
- Semantics of timed systems.
Research Focus under Alberto Sangiovanni-Vincentelli:
- Contract-based design for CPS.
- Automotive electronics architecture (sensors, actuators, computing, connectivity, control) design.
- Security/safety for automotive systems.
- Platform-based design methodology for swarm systems.
- Model/Data-driven preventive maintenance of 3-D printers.
- Model/Data-driven diagnosis for energy efficient buildings.