Abstract: Our overall aim in this project is to synthesize desired behaviors in populations of bacterial and mammalian cells. To this goal, we define the basis of a next-generation CPS called biological CPS (bioCPS). The enabling technologies are synthetic biology and micron-scale mobile robotics. Synthetic gene circuits for decision making and local communication among the cells are automatically synthesized using a Bio- Design Automation (BDA) workflow.

Visual identification of structural flaws is quite valuable not only to predict an imminent collapse of a bridge, but also to determine effective precautionary measures and repairs.

Abstract: This project features conception, design, and deployment of a wireless network of embedded devices, for monitoring the behavior of animals in the wild.  The system is being deployed and tested in biologically relevant scenarios.

Abstract: The goal of this research project is to create a scalable and robust cyber-physical system (CPS) framework for the observation and control of the functional interdependencies between bridge structures (stationary physical systems) and trucks (mobile physical agents).  Figure 1 shows the architecture of the proposed CPS framework for the observation and control of truck loads imposed on highway bridges.  While many accomplishments have been achieved during the first year of the project, this poster pres

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Abstract: Cyber-physical systems (CPS) have become increasingly prevalent in applications including health care, energy, and transportation. The tight coupling between cyber and physical components of CPS implies that cyber attacks can degrade the safety, availability, and performance of physical components. The cyber components also introduce multiple entry points to the CPS, lowering the cost of attacks compared to purely physical systems.

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. To this end, we propose a modeling, theoretical, and experimental collaborative effort combining human factors, control theory, and computer science. As crashes at traffic intersections account for about 40% of overall vehicle crashes, we will focus on intersection crashes in this project.

Abstract: In order to improve the current capabilities of automotive active safety control systems (ASCS) one needs to take into account the interactions between driver/vehicle/ASCS/environment. To achieve this goal, this research will infer longterm and short-term driver behavior via the use of Bayesian networks and neuromorphic algorithms to estimate the driver’s skills and current state of attention from eye movement data, together with dynamic motion cues obtained from steering and pedal inputs.

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Abstract: This project addresses highly dynamic Cyber-Physical Systems (CPSs) understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of advanced safety systems on passenger cars, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives.