Loss of walking function and leg sensation are devastating consequences of spinal cord injury (SCI). These deficits have a profoundly negative impact on independence and quality of life of those affected. Moreover, wheelchair reliance after SCI increases the risk of medical complications. The healthcare costs associated with SCI are ~$50 billion/year, presenting a significant public health concern. Currently, there are no biomedical solutions capable of restoring walking and leg sensation after SCI.

This work examines how to get safety and security in Internet of Things (IoT) systems where multiple devices (things), each designed in isolation from others, are brought together to form a networked system, controlled via one or more software applications ("apps"). "Things" in an IoT environment can include simple devices such as switches, lightbulbs, smart locks, thermostats, and safety alarms as well as complex systems such as appliances, smartphones, and cars.

The goal of this project is to develop an automated assistive device capable of restoring walking and standing functions in persons with motor impairments. Although research on assistive devices, such as active and passive orthoses and exoskeletons, has been ongoing for several decades, the improvements in mobility have been modest due to a number of limitations. One major challenge has been the limited ability to sense and interpret the state of the human, including volitional motor intent and fatigue.

Smart manufacturing integrates information, technology, and human ingenuity to inspire the next revolution in the manufacturing industry. Manufacturing has been identified as a key strategic investment area by the U.S. government, private sector, and university leaders to spur innovation and keep America competitive. However, the lack of new methodologies and tools is challenging continuous innovation in the smart manufacturing industry.

Data-driven cyber-physical systems are ubiquitous in many sectors including manufacturing, automotive, transportation, utilities and health care. This project develops the theory, methods and tools necessary to answer the central question "how can we, in a data-rich world, design and operate cyber-physical systems differently?" The resulting data-driven techniques will transform the design and operation process into one in which data and models - and human designers and operators - continuously and fluently interact. This integrated view promises capabilities beyond its parts.

One of the challenges toward achieving the vision of smart cities is improving the state of the underground infrastructure. For example, large US cities have thousands of miles of aging water mains, resulting in hundreds of breaks every year, and a large percentage of water consumption that is unaccounted for. The goal of this project is to develop models and methods to generate, analyze, and share data on underground infrastructure systems, such as water, gas, electricity , and sewer networks.

Smart manufacturing integrates information, technology, and human ingenuity to inspire the next revolution in the manufacturing industry. Manufacturing has been identified as a key strategic investment area by the U.S. government, private sector, and university leaders to spur innovation and keep America competitive. However, the lack of new methodologies and tools is challenging continuous innovation in the smart manufacturing industry.

Factories, chemical plants, automobiles, and aircraft have come to be described today as cyber-physical systems of systems--distinct systems connected to form a larger and more complex system. For many such systems, correct operation is critical to safety, making their security of paramount importance. Unfortunately, because of their heterogeneous nature and special purpose, it is very difficult to determine whether a malicious attacker can make them behave in a manner that causes harm.

This research team envisions that connected testbeds, i.e., remotely accessible testbeds integrated over a network in closed loop, will provide an affordable, repeatable, scalable, and high-fidelity solution for early cyber-physical evaluation of connected automated vehicle (CAV) technologies. Engineering testbeds are critical for empirical validation of new concepts and transitioning new theory to practice. However, the high cost of establishing new testbeds or scaling the existing ones up hinders their wide utilization.