OARS funding Systems

Cyber-physical systems (CPS) are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. Advances in CPS will enable capability, adaptability, scalability, resiliency, safety, security, and usability that will far exceed the simple embedded systems of today. CPS technology will transform the way people interact with engineered systems -- just as the Internet has transformed the way people interact with information. New smart CPS will drive innovation and competition in sectors such as agriculture, energy, transportation, building design and automation, healthcare, and manufacturing.

On behalf of the Governor's Office of Health Transformation (OHT), and the Ohio Departments of Medicaid (ODM), Health (ODH) and Higher Education (ODHE), the Ohio Colleges of Medicine Government Resource Center (GRC) is requesting applications from qualified investigators through the Infant Mortality (IM) Research Partnership to identify interventions and resources needed to improve health outcomes for underserved populations and address the complicated health issue of infant mortality from a systems perspective. The IM Research Partnership seeks to fund multiple research projects in areas including but not limited to: systems dynamics modeling of the impact of the following efforts on infant mortality: improved access to care, safe sleep, and impact of progesterone; predictive modeling for infant mortality; spatial GIS modeling for identifying high-risk communities; and evaluation of the impact of OIMRI home visiting programs.

DARPA Defense Sciences Office (DSO) wants to identify and pursue high-risk, high-payoff research initiatives across a broad spectrum of science and engineering disciplines and to transform these initiatives into important, radically new, game-changing technologies for U.S. national security. The current overarching office themes include accelerating scientific discovery, exploring fundamental limits, and expecting the unexpected. In support of this mission, the DSO Office-wide BAA invites proposers to submit innovative basic or applied research concepts in one or more of the following technical areas: Mathematics, Modeling and Design; Physical Systems; Human-Machine Systems; and Social Systems. Each of these areas is described below and includes a list of example research topics that highlight several (but not all) potential areas of interest. Proposals must investigate innovative approaches that enable revolutionary advances. DSO is explicitly not interested in approaches or technologies that primarily result in evolutionary improvements to the existing state of practice.

The Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) program supports academe-industry partnerships which are led by an interdisciplinary academic research team collaborating with a least one industry partner. In this program, there is a heavy emphasis on the quality, composition, and participation of the partners, including their appropriate contributions. These partnerships focus on the integration of technologies into a specified human-centered service system with the potential to achieve transformational benefits, satisfying a real need by making an existing service system smart(er) or by spurring the creation of an entirely new smart service system. The selected service system should function as a test bed. PFI:BIC funds research partnerships working on projects that operate in the post-fundamental/translational space; the proposers must be mindful of the state of the art and the competitive landscape. However, a clear path to commercialization does not need to be a central part of this proposal. These projects require additional effort to integrate the technology into a real service system, incorporating human factors considerations to assure the system's efficacy. The research tasks in turn might spawn additional discoveries inspired by this interaction of humans with the technology.

The Dynamics, Control and Systems Diagnostics (DCSD) program supports fundamental research on the analysis, measurement, monitoring and control of dynamic systems, including development of new analytical, computational and experimental tools, and novel applications to engineered and natural systems. Dynamics is the science of systems that change in time. Control concerns the use of external influences to produce desired dynamic behaviors. Systems diagnostics concerns the use of observation to infer information about a dynamic system. Objectives of the DCSD program are the discovery of new phenomena and the investigation of innovative methods and applications in dynamics, control and diagnostics. The intellectual merit of proposals submitted to the DCSD program will be evaluated on the basis of fundamental innovation in foundational areas of dynamics and control, and on the potential for transformative impact within and across disciplinary boundaries. Proposals submitted to the DCSD program should be aligned with the disciplinary thrusts of the CMMI division. For example, innovative research that primarily concerns electromagnetic or chemical phenomena should be directed to the ECCS or CBET divisions. To ensure that a project is appropriate for the DCSD program, PIs are very strongly encouraged to email a project summary of approximately 250 words to the DCSD Program Directors prior to the full submission. The DCSD Program does not fund fundamental research relating to sensing modalities or sensor development. Proposals offering fundamental research on sensing modalities should be submitted to the Communications, Circuits and Sensing Systems (CCSS) program or the Electronics, Photonics, and Magnetic Devices (EPMD) program in the ECCS Division.

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 Office of Basic Energy Sciences (BES) of the U.S. Department of Energy (DOE) announces its interest in receiving applications in Computational Materials Sciences proposing integrated, multidisciplinary teams that will perform research to develop validated community codes and data bases for predictive design of functional materials, excluding structural materials. Computational Materials Sciences Teams could also involve new approaches to enhance the use of large data sets derived from advanced characterization of materials, materials synthesis, processing, and properties assessments and the parallel data that are generated by large scale computational efforts that model materials phenomena. Computational Materials Sciences will support the Materials Genome Initiative for Global Competitiveness (MGI) that was announced by the President in June 2011. The goal of the MGI is to reduce the time from discovery to deployment of new materials by a factor of two and is tied to advancement of American manufacturing capability. This funding opportunity continues the BES commitment to the MGI and the development of open source codes that can take full advantage of today's petascale and future exascale leadership computing facilities.

The Office of Basic Energy Sciences (BES) of the U.S. Department of Energy (DOE) announces its interest in receiving applications in Computational Materials Sciences proposing integrated, multidisciplinary teams that will perform research to develop validated community codes and data bases for predictive design of functional materials, excluding structural materials. Computational Materials Sciences Teams could also involve new approaches to enhance the use of large data sets derived from advanced characterization of materials, materials synthesis, processing, and properties assessments and the parallel data that are generated by large scale computational efforts that model materials phenomena. Computational Materials Sciences will support the Materials Genome Initiative for Global Competitiveness (MGI) that was announced by the President in June 2011. The goal of the MGI is to reduce the time from discovery to deployment of new materials by a factor of two and is tied to advancement of American manufacturing capability. This funding opportunity continues the BES commitment to the MGI and the development of open source codes that can take full advantage of today's petascale and future exascale leadership computing facilities.

The NSF/Intel Partnership on Computer Assisted Programming for Heterogeneous Architectures (CAPA) aims to address the problem of effective software development for diverse hardware architectures through groundbreaking university research that will lead to a significant, measurable leap in software development productivity by partially or fully automating software development tasks that are currently performed by humans. The main research objectives for CAPA include programmer effectiveness, performance portability, and performance predictability. In order to address these objectives, CAPA seeks research proposals that explore (1) programming abstractions and/or methodologies that separate performance-related aspects of program design from how they are implemented; (2) program synthesis and machine learning approaches for automatic software construction that are demonstrably correct; (3) advanced hardware-based cost models and abstractions to support multi-target code generation and performance predictability for specified heterogeneous hardware architectures; and (4) integration of research results into principled software development practices.

The SNM-IS solicitation seeks proposals that investigate novel scalable nanomanufacturing and integration methods for nano-enabled integrated systems with a clear commercial relevance. Proposals should consider addressing key aspects of the nanomanufacturing value chain comprised of nano-scale building-blocks → complex nanomaterials and nanostructures → functional components and devices → integrated sub-systems and systems

The Scalable Parallelism in the Extreme (SPX) program aims to support research addressing the challenges of increasing performance in this modern era of parallel computing. This will require a collaborative effort among researchers in multiple areas, from services and applications down to micro-architecture. SPX encompasses all five NSCI Strategic Objectives, including supporting foundational research toward architecture and software approaches that drive performance improvements in the post-Moore's Law era; development and deployment of programmable, scalable, and reusable platforms in the national HPC and scientific cyberinfrastructure ecosystem; increased coherence of data analytic computing and modeling and simulation; and capable extreme-scale computing. Coordination with industrial efforts that pursue related goals are encouraged.

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.

The Dynamics, Control and Systems Diagnostics (DCSD) program supports fundamental research on the analysis, measurement, monitoring and control of dynamic systems, including development of new analytical, computational and experimental tools, and novel applications to engineered and natural systems. Dynamics is the science of systems that change in time. Control concerns the use of external influences to produce desired dynamic behaviors. Systems diagnostics concerns the use of observation to infer information about a dynamic system. Objectives of the DCSD program are the discovery of new phenomena and the investigation of innovative methods and applications in dynamics, control and diagnostics. The intellectual merit of proposals submitted to the DCSD program will be evaluated on the basis of fundamental innovation in foundational areas of dynamics and control, and on the potential for transformative impact within and across disciplinary boundaries.

Researchers in all fields of science and engineering are being challenged in two key directions.  The first challenge is to push beyond the current boundaries of knowledge to provide ever-deeper insights through fundamental disciplinary research by addressing increasingly complex questions, which often requires extremely sophisticated integration of theoretical, experimental, observational and simulation and modeling results.   These efforts, which have relied heavily on observing platforms and other data collection efforts, computing facilities, software, advanced networking, analytics, visualization and models have led to important breakthroughs in all areas of science and engineering and represent a very strong bottom-up approach to the necessary research infrastructure.  The second, and more extensive challenge, is to synthesize these fundamental ground breaking efforts across multiple fields to transform scientific research into an endeavor that integrates the deep knowledge and research capabilities developed within the universities, industry and government labs. Individuals, teams and communities need to be able work together; likewise, instruments, facilities (including MREFCs), datasets, and cyber-services must be integrated from the group to campus to national scale. One can imagine secure, geographically distributed infrastructure components including advanced computing facilities, scientific instruments, software environments, advanced networks, data storage capabilities, and the critically important human capital and expertise. Greater understanding is also needed of how scientific and research communities will evolve in the presence of new cyberinfrastructure. 

SoftwareInfrastructure for Sustained Innovation (SI2) is a long-term investment focused on realizing a portion of the Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504730) vision and catalyzing new thinking, paradigms and practices in science and engineering. CIF21 envisions a linked cyberinfrastructure architecture that integrates large-scale computing, high-speed networks, massive data archives, instruments and major facilities, observatories, experiments, and embedded sensors and actuators, across the nation and the world, and that enables research at unprecedented scales, complexity, resolution, and accuracy by integrating computation, data, and experiments in novel ways. Software is a primary modality through which CIF21 innovation and discovery will be realized. It permeates all aspects and layers of cyberinfrastructure (from application codes and frameworks, programming systems, libraries and system software, to middleware, operating systems, networking and the low-level drivers). The CIF21 software infrastructure must address the complexity of this cyberinfrastructure, accommodating: disruptive hardware trends; ever-increasing data volumes; data integrity, privacy, and confidentiality; security; complex application structures and behaviors; and emerging concerns such as fault-tolerance and energy efficiency. The programs must focus on building robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery.
 The Division of Advanced Cyberinfrastructure in the Computer & Information Science & Engineering Directorate (CISE/ACI) is partnering with Directorates and Offices across the NSF to support SI2, a long-term comprehensive program focused on realizing a sustained software infrastructure that is an integral part of CIF21.

Cyber-physical systems (CPS) are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. Advances in CPS will enable capability, adaptability, scalability, resiliency, safety, security, and usability that will far exceed the simple embedded systems of today. CPS technology will transform the way people interact with engineered systems -- just as the Internet has transformed the way people interact with information. New smart CPS will drive innovation and competition in sectors such as agriculture, energy, transportation, building design and automation, healthcare, and manufacturing.

Cyber-physical systems (CPS) are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. Advances in CPS will enable capability, adaptability, scalability, resiliency, safety, security, and usability that will far exceed the simple embedded systems of today. CPS technology will transform the way people interact with engineered systems -- just as the Internet has transformed the way people interact with information. New smart CPS will drive innovation and competition in sectors such as agriculture, energy, transportation, building design and automation, healthcare, and manufacturing. The December 2010 report of the President's Council of Advisors on Science and Technology (PCAST) titled Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technologycalls for continued investment in CPS research because of its scientific and technological importance as well as its potential impact on grand challenges in a number of sectors critical to U.S. security and competitiveness such as the ones noted above. These challenges and technology gaps are further described in aCPS Vision Statementpublished in 2012 by the federal Networking and Information Technology Research and Development (NITRD) CPS Senior Steering Group. Tremendous progress has been made in advancing CPS technology over the last five-plus years. We have explored foundational technologies that have spanned an ever-growing set of application domains, enabling breakthrough achievements in many of these fields. At the same time, the demand for innovation in these domains continues to grow, and is driving the need to accelerate fundamental research to

Together with University Advancement, the Office for the Advancement of Research & Scholarship (OARS) is rolling out an new crowdfunding platform called HawksNest. Through HawksNest, alumni, family, and friends of the university can directly support the research, scholarship, and service projects of Miami University students, faculty, and staff. This is how HawksNest works: * Any Miami University student, faculty, or staff member may complete an online application to have a project considered for funding. * An internal review team assesses applications and posts approved projects on HawksNest for a maximum of 45 days. * Potential donors visit the site to learn about and pledge funds to approved projects. * Once a funding goal has been met, the project can begin! * Project managers use the site to keep donors up-to-date with information on the project's progress.

CISE’s Division of Computer and Network Systems (CNS) supports research and education projects that develop new knowledge in two core programs:Computer Systems Research (CSR) program; andNetworking Technology and Systems (NeTS) program.Proposers are invited to submit proposals in three project classes, which are defined as follows:Small Projects - up to $500,000 total budget with durations up to three years;Medium Projects - $500,001 to $1,200,000 total budget with durations up to four years; andLarge Projects - $1,200,001 to $3,000,000 total budget with durations up to five years.A more complete description of the three project classes can be found in section II. Program Description of this document.

The scope is science and technology development, experimentation, and demonstration in the areas of improving and personalizing individual, team, and larger instructional training methods to include the following: - Competency definition and requirements analysis - Measuring, diagnosing, and modeling human expertise and performance - Rapid development of models of human cognition - Specifying and validating, both empirically and practically, new classes of synthetic, computer-generated agents and teammates - Training and rehearsal strategies and models - Environments that support learning and proficiency achievement and sustainment during non-practice or under novel contexts

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.