Group items tagged

The purpose of this program is to develop next generation health care solutions and encourage existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as sensor technology, networking, information and machine learning technology, decision support systems, modeling of behavioral and cognitive processes, as well as system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, social interactions, cognitive limitations, barriers to behavioral change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems. Such solutions demand multidisciplinary teams ready to address technical, behavioral and clinical issues ranging from fundamental science to clinical practice.

The purpose of this program is to develop next generation health care solutions and encourage existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as sensor technology, networking, information and machine learning technology, decision support systems, modeling of behavioral and cognitive processes, as well as system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, social interactions, cognitive limitations, barriers to behavioral change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems. Such solutions demand multidisciplinary teams ready to address technical, behavioral and clinical issues ranging from fundamental science to clinical practice.

The Platforms for Advanced Wireless Research (PAWR) program aims to support advanced wireless research platforms conceived by the U.S. academic and industrial wireless research community. PAWR will enable experimental exploration of robust new wireless devices, communication techniques, networks, systems, and services that will revolutionize the nation's wireless ecosystem, thereby enhancing broadband connectivity, leveraging the emerging Internet of Things (IoT), and sustaining US leadership and economic competitiveness for decades to come.

The Smart and Autonomous Systems (S&AS) program focuses on Intelligent Physical Systems (IPS) that are cognizant, taskable, reflective, ethical, and knowledge-rich. The S&AS program welcomes research on IPS that are aware of their capabilities and limitations, leading to long-term autonomy requiring minimal or no human operator intervention. Example IPS include, but are not limited to, robotic platforms and networked systems that combine computing, sensing, communication, and actuation. Cognizant IPS exhibit high-level awareness beyond primitive actions, in support of persistent and long-term autonomy. Taskable IPS can interpret high-level, possibly vague, instructions, translating them into concrete actions that are dependent on the particular context in which the IPS is operating. Reflective IPS can learn from their own experiences and those of other entities, such as other IPS or humans, and from instruction or observation; they may exhibit self-aware and self-optimizing capabilities. Ethical IPS should adhere to a system of societal and legal rules, taking those rules into account when making decisions. Knowledge-rich IPS employ a variety of representation and reasoning mechanisms, such as semantic, probabilistic and commonsense reasoning; are cognitively plausible; reason about uncertainty in decision making; and reason about the intentions of other entities in decision making.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

The goal of the Smart and Connected Health (SCH) Program is to accelerate the development and use of innovative approaches that would support the much needed transformation of healthcare from reactive and hospital-centered to preventive, proactive, evidence-based, person-centered and focused on well-being rather than disease. Approaches that partner technology-based solutions with biobehavioral health research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next generation health care solutions and encourage existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as sensor technology, networking, information and machine learning technology, decision support systems, modeling of behavioral and cognitive processes, as well as system and process modeling.

The Civil Infrastructure Systems (CIS) program supports research leading to the engineering of infrastructure systems for resilience and sustainability without excluding other key performance issues.  Areas of interest include intra- and inter-physical, information and behavioral dependencies of infrastructure systems, infrastructure management, construction engineering, and transportation systems.  Special emphasis is on the design, construction, operation, and improvement of infrastructure networks with a focus on systems engineering and design, performance management, risk analysis, life-cycle analysis, modeling and simulation, behavioral and social considerations not excluding other methodological areas or the integration of methods. This program does not encourage research proposals primarily focused on structural engineering, materials or sensors that support infrastructure system design, extreme event modeling, hydrological engineering, and climate modeling, since they do not fall within the scope of the CIS program.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) applied researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of the algorithmic contributions and resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

Computing systems have undergone a fundamental transformation from the single-core processor-devices of the turn of the century to today's ubiquitous and networked devices with multi-core/many-core processors along with warehouse-scale computing via the cloud. At the same time, semiconductor technology is facing fundamental physical limits and single-processor performance has plateaued. This means that the ability to achieve performance improvements through improved processor technologies alone has ended. In recognition of this obstacle, the recent National Strategic Computing Initiative (NSCI) encourages collaborative efforts to develop, "over the next 15 years, a viable path forward for future high-performance computing (HPC) systems even after the limits of current semiconductor technology are reached (the 'post-Moore's Law era')."

This program seeks to prepare, nurture, and grow the national scientific research workforce for creating, utilizing, and supporting advanced cyberinfrastructure (CI) to enable and potentially transform fundamental science and engineering research and contribute to the Nation's overall economic competitiveness and security. The goals of this solicitation are to (i) ensure broad adoption of CI tools, methods, and resources by the research community in order to catalyze major research advances and to enhance researchers' abilities to lead the development of new CI; and (ii) integrate core literacy and discipline-appropriate advanced skills in advanced CI as well as computational and data-driven science and engineering into the Nation's educational curriculum/instructional material fabric spanning undergraduate and graduate courses for advancing fundamental research. Pilot and Implementation projects may target one or both of the solicitation goals, while Large-scale Project Conceptualization projects must address both goals. For the purpose of this solicitation, advanced CI is broadly defined as the set of resources, tools, methods, and services for advanced computation, large-scale data handling and analytics, and networking and security for large-scale systems that collectively enable potentially transformative fundamental research.

This Funding Opportunity Announcement (FOA) encourages research project grant (R01) applications to leverage large-scale, real-world data from electronic health records (EHRs) from a variety of systems (e.g., the Department of Defense (DOD), Department of Veterans Affairs (VA), Centers for Medicare and Medicaid Services administrative claims, as well as public or private health care systems and networks) to understand risk, onset, course, and impact of treatments and services for mental and neurological disorders and to identify promising new mental health and neurological disorders research. There is particular interest in leveraging EHRs and administrative data to 1) understand and improve the treatment of post traumatic psychopathology, including posttraumatic stress disorder, depression, traumatic brain injury (TBI), and risk for suicide; and 2) characterize post-trauma multi-symptom recovery trajectory patterns of TBI, that may include post traumatic stress disorder, depression, cognitive impairment, pain, substance abuse disorder and risk for suicide. NIMH also invites innovative approaches to use EHR and administrative data to understand risk, onset, course, and impact of treatments and services for mental disorders more broadly.

The High Priority(HP) Grant Program is a discretionary (i.e., competitive) program which provides financial assistance to: 1)The HP-ITD projects which include the deployment of intelligent transportation system applications for CMV operations; support/maintenance of CMV information systems/networks, the linking of FMCSA and state information systems, the improvement of safety and productivity of CMVs and commercial drivers and the reduction of costs associated with CMV operations and regulatory requirements. The High Priority(HP) Grant Program is a discretionary (i.e., competitive) program which provides financial assistance to: 2)The HP-CMV projects which include the augmentation of motor carrier safety projects planned in accordance with the Motor Carrier Safety Assistance Program (MCSAP),as well as projects related to Performance and Registration Information Systems Management (PRISM) and State Safety Data Quality (SSDQ).

The Campus Cyberinfrastructure (CC*) program invests in coordinated campus-level networking and cyberinfrastructure improvements, innovation, integration, and engineering for science applications and distributed research projects. Learning and workforce development (LWD) in cyberinfrastructure is explicitly addressed in the program. Science-driven requirements are the primary motivation for any proposed activity.

Humanity depends upon the Earth's physical resources and natural systems for food, energy, and water (FEW). However, both the physical resources and the FEW systems are under increasing stress. It is becoming imperative that we determine how society can best integrate social, ecological, physical and built environments to provide for growing demand for food, energy and water in the short term while also maintaining appropriate ecosystem services for the future. Known stressors in FEW systems include governance challenges, population growth and migration, land use change, climate variability, and uneven resource distribution. The interconnections and interdependencies associated with the FEW Nexus pose research grand challenges. To meet these grand challenges, there is a critical need for research that enables new means of adapting societal use of FEW systems. The INFEWS program seeks to support research that conceptualizes FEW systems broadly and inclusively, incorporating social and behavioral processes (such as decision making and governance), physical processes (such as built infrastructure and new technologies for more efficient resource utilization), natural processes (such as biogeochemical and hydrologic cycles), biological processes (such as agroecosystem structure and productivity), and cyber-components (such as sensing, networking, computation and visualization for decision-making and assessment). Investigations of these complex systems may produce discoveries that cannot emerge from research on food or energy or water systems alone. It is the synergy among these components in the context of sustainability that will open innovative science and engineering pathways to produce new knowledge, novel technologies, and innovative predictive capabilities.

Humanity depends upon the Earth's physical resources and natural systems for food, energy, and water (FEW). However, both the physical resources and the FEW systems are under increasing stress. It is becoming imperative that we determine how society can best integrate social, ecological, physical and built environments to provide for growing demand for food, energy and water in the short term while also maintaining appropriate ecosystem services for the future. Known stressors in FEW systems include governance challenges, population growth and migration, land use change, climate variability, and uneven resource distribution.The interconnections and interdependencies associated with the FEW Nexus pose research grand challenges. To meet these grand challenges, there is a critical need for research that enables new means of adapting societal use of FEW systems. The INFEWS program seeks to support research that conceptualizes FEW systems broadly and inclusively, incorporating social and behavioral processes (such as decision making and governance), physical processes (such as built infrastructure and new technologies for more efficient resource utilization), natural processes (such as biogeochemical and hydrologic cycles), biological processes (such as agroecosystem structure and productivity), and cyber-components (such as sensing, networking, computation and visualization for decision-making and assessment).

The Electrical, Communications and Cyber Systems Division (ECCS) supports enabling and transformative engineering research at the nano, micro, and macro scales that fuels progress in engineering system applications with high societal impact. This includes fundamental engineering research underlying advanced devices and components and their seamless penetration in power, controls, networking, communications or cyber systems. The research is envisioned to be empowered by cutting-edge computation, synthesis, evaluation, and analysis technologies and is to result in significant impact for a variety of application domains in healthcare, homeland security, disaster mitigation, telecommunications, energy, environment, transportation, manufacturing, and other systems-related areas. ECCS also supports new and emerging research areas encompassing 5G and Beyond Spectrum and Wireless Technologies, Quantum Information Science, Artificial Intelligence, Machine Learning, and Big Data.