Abstract: Recent years have seen medical devices go from being monolithic to a collection of integrated systems. Modern medical device systems have thus become a distinct class of cyber-physical systems called Medical Cyber Physical Systems (MCPS), featuring complex and close interaction of sophisticated treatment algorithms with the physical aspects of the system, and especially the patient whose safety is of the utmost concern. The goal of this project is to develop a new paradigm for the design and implementation of safe, secure, and reliable MCPS, which includes:

Abstract: The objective of this study is to develop a high-performance and robust neural-machine interface (NMI) for artificial legs, which can accurately and reliably identify user intent in real-time.

Abstract: Cyber-Physical Systems (CPS) are deployed in a wide variety of safety critical applications from avionics, medical, and automotive domains. For these applications, it is essential to create a precise specification and formally verify that the implementation behaves as specified. The formal verification of these systems presents a wide variety of challenges. Models of these systems must represent the physical world, analog sensors and actuators, computer hardware and software, networks, and feedback control.

Abstract: Motivation: Energy infrastructure is a critical underpinning of modern society. To ensure its reliable operation, a nation-­‐wide or continent-­‐wide situational awareness system is essential to provide high-­‐resolution understanding of the system dynamics such that proper actions can be taken in real-­‐time in response to power system disturbances and to avoid cascading blackouts. The power grid represents a typical highly dynamic cyber-­‐physical system (CPS).

Abstract: Multicore platforms have the potential of revolutionizing the capabilities of embedded cyber-physical systems but lack predictability in execution time due to shared resources. Safety-critical systems require such predictability for certification. This research aims at resolving this multicore "predictability problem.'' It will develop methods that enable to share hardware resources to be allocated and provide predictability, including support for real-time operating systems, middleware, and associated analysis tools.

Abstract: Today, the assembly of safety-critical software involves many distinct agents, including control engineers and software engineers. Due in part to the existing regulatory framework, little, if any, semantic information is passed from control engineers (who specify the real-time software) to software engineers (who implement the specifications). As a result, high-level, system-wide information is lost at the time of software assembly, and only during system validation do software specification and semantics re-appear.

Abstract: Processors in cyber‐physical systems are increasingly being used in applications where they must operate in harsh ambient conditions and a computational workload which can lead to high chip temperatures. Examples include cars, robots, aircraft and spacecraft. High operating temperatures accelerate the aging of the chips, thus increasing transient and permanent failure rates. Current ways to deal with this mostly turn off the processor core or drastically slow it down when some part of it is seen to exceed a given temperature threshold.

Abstract: Critical infrastructure systems – electricity grids, transportation networks, gas and water distribution networks – serve the needs of millions of people with extraordinary reliability. These large-scale systems comprise 106 − 108 individual elements (humans and hardware) whose actions are inconsequential in isolation but profoundly important in aggregate. This proposal focuses on coordination of these elements in smart infrastructure systems with integrated ubiquitous sensing, communications, computation, and control.

Abstract: A primary objective of this research is to establish a foundational framework for smart grids that enables significant penetration of renewable DERs and facilitates flexible deployments of plug-and-play applications.  Under this common theme, the PIs have taken a data analytics perspective to explore rigorous approaches in modeling, optimization, and control of wind generation integration.

Abstract: The goal of this project is to develop fundamental theory, computationally efficient algorithms, and real- world experiments for the analysis and design of safety-critical cyber-physical transportation systems with human operators. We envision a nearby future in which roads will be populated by networks of smart vehicles that will cooperate with each other, with the surrounding infrastructure, and with their drivers to make transportation safer, more enjoyable, and more efficient.