State-of-the-art systems engineering is model-based: models are used in all phases of systems’ lifecycle. An exciting new research direction focuses on symbiotic design where human-driven model-based design processes are complemented by AI/ML assisted components. Our research covers a broad range of engineering activities where models and data are used both in design and in operations.

Cyber-physical systems and human cyber-physical systems where humans and computing are tightly integrated into a physical environment
Design-space exploration, both parametric and combinatorial, with optimization and trade-offs
Fault diagnostics and prognostics, system health management
Foundations for Model-integrated Computing / Model-driven design: meta-programmable modeling tools, formal frameworks, domain-specific modeling languages, model transformations, and run-time environments for model-driven system development
Model integration platforms for physical and biological systems
Resilient systems that can recover from faults of cyber-effects and continue operating
Assurance of Cyber-physical systems with learning-enabled components
Software engineering environments for agile and adaptive system development
System verification and validation, including both formal and coverage-driven methods
Large-scale heterogeneous simulation environments for studying complex, emerging behaviors in system-of-systems

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Cyber-Physical Systems Virtual Organization: Active Resources

The Cyber-Physical Systems Virtual Organization (CPS-VO) was founded by NSF in 2010 to: (i)facilitate and foster interaction and exchanges among CPS PIs and their teams; (ii) enable sharing of artifacts and knowledge generated by the projects with the broader engineering and scientific communities; and (iii) facilitate and foster collaboration and information exchange between CPS researchers and industry. During the last five years, the CPS-VO has become the focal point of the CPS community in the US and it has played a significant role in catalyzing CPS research world-wide.

Spatio-Temporal AI Inference Engines for System-Level Reliability

SCC-IRG Track 1: Mobility for all - Harnessing Emerging Transit Solutions for Underserved Communities

Public transportation infrastructure is an essential component in cultivating equitable communities. However, public transit agencies have historically struggled to achieve this since they are often severely stressed in terms of resources as they have to make the trade-off between concentrating service into routes that serve large numbers of people and spreading service out to ensure that people everywhere have access to at least some service.

NeTS: JUNO2: STEAM: Secure and Trustworthy Framework for Integrated Energy and Mobility in Smart Connected Communities

The rapid evolution of data-driven analytics, Internet of things (IoT) and cyber-physical systems (CPS) are fueling a growing set of Smart and Connected Communities (SCC) applications, including for smart transportation and smart energy. However, the deployment of such technological solutions without proper security mechanisms makes them susceptible to data integrity and privacy attacks, as observed in a large number of recent incidents. If not addressed properly, such attacks will not only cripple SCC operations but also influence the extent to which customers are willing to share data.

EdgeNet: An online Edge Computing Based Generative Anomaly Detection and Prognostics Solution for Networked Equipment at Customer Premises

Anomaly detection, prognostication and automated mitigation are very critical for data center management. Most of these approaches can be divided into two categories - model-based and data-driven. While model-based techniques rely on physics guided models that can explain and predict the expected progression of parameters such as temperature and voltage in electronics, the data-driven approach is suitable for complex scenarios where a suitable physics based model is unavailable. The data-driven approaches can be further divided into supervised and unsupervised methods.

AI-Engine for Optimizing Integrated Service Mixed Fleet Transit Operations

In every public transit system, a trade-off has to be made between concentrating service into very useful routes that serve large numbers of people and spreading service out to ensure that people everywhere have access to at least some service. Improving the efficiency of an existing system while enhancing service in terms of both usefulness and coverage presents considerable challenges.

Collaborative Research: NSCI Framework: Software for Building a Community-Based Molecular Modeling Capability Around the Molecular Simulation Design Framework (MoSDeF)

Rapid Scenario-Driven Integrated Simulation Experimentation Framework

Cyber-Physical Systems (CPS) are composed of a wide range of networked physical, computational, and human/organization components. These systems are highly complex as they have many different heterogeneous components, such as physical, computational, and human. Simulation-based evaluation of the behavior of CPS is complex, as it involves multiple, heterogeneous, interacting domains. Each simulation domain has sophisticated tools, but their integration into a coherent framework is a difficult, time-consuming, labor-intensive, and error-prone task.

Digital Twin Technologies to Improve Mission Readiness and Sustainment

Cybersecurity Evaluation Framework for Industrial Control Systems

Evaluating the cybersecurity of a complex Industrial Control Systems (ICS), such as the Railway Transportation System (RTS), against a variety of cyber threats is a significantly hard and multi-faceted problem.

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