The safety and performance of cyber-physical systems (CPS) depend crucially on control and scheduling decisions that often are fixed at design time, which significantly restricts the conditions under which a system can operate both safely and with suitable performance. Going beyond prior work that has explored different control and scheduling adaptations in individual system designs, this project will conduct more general and in-depth investigations, into how cyber-physical systems?

Microbial pathogen transmission in buildings is an urgent public health concern. The pandemic of coronavirus disease 2019 (COVID-19) adds to the urgency of developing effective means to reduce pathogen transmission in public buildings with minimal disruptions in building functions. With the ultimate goal to develop healthy buildings that minimize risks of infectious diseases, this project will develop smart control strategies for buildings and assistive robots to mitigate pathogen transmission and occupant exposure.

The proposed research focuses on harnessing the growing fitness spaces in support of form, performance and injury prevention in exercise, therapy, and rehabilitation. The ability to monitor body dynamics and to provide real-time feedback is instrumental in fitness training and injury prevention. Motivated by the lack of fitness training models that understand the key factors related to human motion in the cyber realm, this project aims to leverage the cyber-physical components of fitness monitoring to track and encourage proper movement during strength training.

Motivated by the rising caregiver burden and challenges in remote health behavior monitoring, the proposed research will enable effective assistive interventions in response to dynamically changing health behaviors for target populations. To be effective and impactful, assistive mechanisms need to capture and respond to the subtle and changing context of the human. Human behaviors, however, are challenging to learn due to their complexity and the constantly changing physical, social, and environmental context.

Advances in artificial intelligence (AI) make it clear that intelligent systems will account for the next leap in scientific progress to enable a myriad of future applications that improve the quality of life, contribute to the economy, and enhance societal resilience to a broad spectrum of disruptions. Yet, advances in AI come at a considerable resource costs. To reduce the cost of AI, this project takes inspiration from biological systems. It is well-known that a key bottleneck in AI is the perception subsystem.

Modern society relies heavily on systems that operate within strict timing requirements such as in engine control units in automobiles, aircraft avionics and navigation systems, programmable logic controllers in manufacturing plants, industrial control systems in the electricity sector, and many hundreds of others. The recent advent of autonomous cars, drones and internet-of-things (IoT) further expands the reach of these "real-time systems".

Computing systems that engage people physically with high degrees of autonomy need to provide rigorous guarantees of safety. Formal methods can been used on such systems to provide mathematical proofs to ensure correct behavior. However, machine learning and data-driven approaches are now an indispensable part of autonomous-systems design, and their reliance on highly nonlinear continuous functions and probabilistic reasoning has largely been at odds with the logical and symbolic-analysis frameworks in formal methods.

There is no question that indoor environments are often uncomfortable or unhealthy for occupants. This is an even more critical issue in healthcare facilities, where patients may experience the stressful effects of poor thermal, luminous, and acoustic environments more acutely. With complementary expertise from engineering and psychology, the proposed research is focused on creating a human-on-the-loop, responsive indoor environmental system with the potential to offer better quality of care in hospitals.

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).