OARS funding Computer

The National Institute of Mental Health (NIMH) with other ICs are issuing this Notice of Intent to Publish a Funding Opportunity Announcement to promote new initiatives that will solicit applications to support research to determine the role and impact of digital health interventions [e.g., mobile health (mhealth), telemedicine and telehealth, health information technology (IT), wearable devices] to address secondary health effects of the social, behavioral, and economic changes following the COVID-19 pandemic, particularly among populations who experience health disparities and vulnerable populations.

As part of our commitment to building the field of data science for social impact, data.org has launched a $10 million data.org Inclusive Growth and Recovery Challenge. Any strong and growing economy requires an inclusive and resilient approach to growth to ensure that talent, innovation, and our communities can become stronger in times of stress. By tapping into the expertise of a broad pool of thinkers and doers, we aim to catalyze innovative and scalable solutions to help individuals and communities thrive, all the while building resilience to withstand future challenges.

The worldwide growth of wireless communication, navigation, and telemetry has provided immense societal benefits including mobile broadband data, Internet of Things (IoT), mobile healthcare, and intelligent transportation systems. These and other applications including 5G and beyond wireless systems call for innovations that can circumvent the challenges of radio spectrum scarcity and interference and foster the growth of ubiquitous, high speed, low latency connectivity. Commercial applications like the above must operate in harmony with scientific uses such as research on radio astronomy, Earth and atmospheric sciences, and must not inhibit weather prediction, polar research, and other nationally vital activities, all of which are dependent upon access to the radio spectrum. The National Science Foundation (NSF) continues to support wireless spectrum research and the scientific uses of the electromagnetic spectrum through multiple programs that enable fast, accurate, dynamic coordination and usage of our limited spectrum resource. These programs have created an opportune ground to build and create a large center-based ecosystem for spectrum research, which is the target of this SII-Center program.

This Research Fund is opening a call for projects in the following areas: * Protecting vulnerable populations from epidemics and catastrophes, including COVID-19: be it migrants, informal settlements, workers in the informal economy, isolated people, people with disabilities, the elderly * Improving data collection and quality in health: how can data and technology help us get out of the crisis, understand it and mitigate it? How can it inform future containment and epidemic control? * Understanding the effects of confinement and social distancing: what are the effects of confinement and social distancing on society and households? What are the mental health consequences? The social and domestic repercussions? * Early warning and preparedness: how do we re-enforce our health infrastructure and ecosystem (including medical devices and drug supply) to be better prepared and how do we protect our health workers and caregivers? * Preserving the environment and our health: connections between climate change, biodiversity loss and the origin of viral disease including socioeconomic dynamics leading to infectious disease outbreaks and sanitary crisis; Learnings from COVID-19 for mitigating future related crises in climate and biodiversity

NSF has long supported transformative research in artificial intelligence (AI) and machine learning (ML). The resulting innovations offer new levels of economic opportunity and growth, safety and security, and health and wellness, intended to be shared across all segments of society. Broad acceptance and adoption of large-scale deployments of AI systems rely critically on their trustworthiness which, in turn, depends on the ability to assess and demonstrate the fairness (including broad accessibility and utility), transparency, explainability, and accountability of such systems. For example, the behavior of algorithms for face recognition, speech, and language, especially when integrated into decision support systems applied across different segments of society, would benefit from new foundational research in fairness of AI systems. NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. Specific topics of interest include, but are not limited to transparency, explainability, accountability, potential adverse biases and effects, mitigation strategies, algorithmic advances, fairness objectives, validation of fairness, and advances in broad accessibility and utility. Funded projects will enable broadened acceptance of AI systems, helping the U.S. further capitalize on the potential of AI technologies. Although Amazon provides partial funding for this program, it will not play a role in the selection of proposals for award.

Scientific machine learning is a core component of artificial intelligence and a computational technology that can be trained, with scientific data, to augment or automate human skills. Major research advances will be enabled by harnessing DOE investments in massive amounts of scientific data, software for predictive models and algorithms, high-performance computing (HPC) and networking platforms, and the national workforce. The crosscutting nature of machine learning and AI provides strong motivation for formulating a prioritized research agenda. Scientific Machine Learning and Artificial Intelligence (Scientific AI/ML) will have broad use and transformative effects across the research communities supported by DOE. Accordingly, a 2019 Basic Research Needs workshop report identified six Priority Research Directions. The first three PRDs describe foundational research themes that are common to the development of Scientific AI/ML methods and correspond to the need for domain-awareness, interpretability, and robustness. The other three PRDs describe capability research themes and correspond to the three major use cases of massive scientific data analysis (PRD #4), machine learning-enhanced

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of artificial intelligence and machine learning in the context of computational decision support for complex systems.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in making research data and artificial intelligence (AI) models findable, accessible, interoperable, and reusable (FAIR1) to facilitate the development of new AI applications in SC's congressionally authorized mission space, which includes the advancement of AI research and development. In particular, ASCR is interested in supporting FAIR benchmark data for AI; and FAIR frameworks for relating data and AI models. For this FOA, AI is inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP). Data, in this context, are the digital artifacts used to generate AI models and/or employed in combination with AI models during inference. An AI model is an inference method that can be used to perform a "task," such as prediction, diagnosis, or classification. The model is developed using training data or other knowledge. An AI task is the inference activity performed by an artificially intelligent system.

Major goals of NSF's D-ISN include: Improve understanding of the operations of illicit supply networks and strengthen the ability to detect, disrupt, and dismantle them. Enhance research communities that effectively integrate operational, computational, social, cultural and economic expertise to provide methods and strategies to combat this complex and elusive global security challenge. Catalyze game-changing technological innovations that can improve discovery and traceability of illicitly sourced products and illicitly sourced labor inputs to products. Provide research outcomes that inform U.S. national security, law enforcement and economic development needs and policies.

The purpose of this Funding Opportunity Announcement (FOA) is to stimulate translation of scientific discoveries and engineering developments in imaging, data science and/or spectroscopic technologies into methods or tools that address contemporary problems in understanding the fundamental biology, potential risk of development, diagnosis, treatment, and/or disease status for cancer or other disease.

The International Research and education Network Connections (IRNC) Base program supports high-performance network connectivity required by international science and engineering research and education collaborations involving the NSF research community. High-performance network connections and infrastructure funded by this program are intended to support science and engineering research and education applications, and preference will be given to solutions that provide the best economy of scale and demonstrate the ability to support the largest communities of interest with the broadest services. Funded projects will assist the U.S. research and education community by enabling state-of-the-art international network services and access to increased collaboration and data services. NSF expects to make 3 to 10 awards in production R&E network infrastructure; 1 to 3 awards in international testbeds; and 1 award in Engagement.

The National Science Foundation (NSF) supports fundamental research and education in science and engineering. NSF's role results in new knowledge and tools as well as a capable, innovative workforce. These complementary building blocks of innovation have led to revolutionary technological advances and wholly new industries. NSF seeks to further develop and nurture a national innovation ecosystem built upon fundamental research that guides the output of scientific and engineering discoveries closer to the development of technologies, products, and services that benefit society. The goal of the NSF Innovation Corps (I-Corps) Program is to use experiential education to help entrepreneurial researchers reduce the time necessary to translate a promising idea from the laboratory bench to widespread implementation. In addition to accelerating technology translation, NSF seeks to reduce the risk associated with technology development conducted without insight into industry requirements and challenges.

To request access to resources of the COVID-19 HPC Consortium, you must prepare a description, no longer than two pages, of your proposed work. To ensure your request is directed to the appropriate resource(s), your description should include the following sections. Do not include any proprietary information in proposals, since your request will be reviewed by staff from a number of consortium sites. It is expected that teams who receive Consortium access will publish their results in the open scientific literature.

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore's Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines increasingly are blurred. Achieving scalability of systems and applications will therefore require coordinated progress in multiple disciplines such as computer architecture, high-performance computing (HPC), programming languages and compilers, security and privacy, systems, theory, and algorithms. Cross-cutting concerns such as performance (including, but not limited to, time, space, and communication resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, and verification), security and privacy, robustness and reliability, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems and application design and implementation.

Address weaknesses in partner nations' export control, investment screening, critical infrastructure protection, customs and border security institutions to prevent malign state actors from exploiting those weaknesses for their advantage.

The worldwide growth of wireless communication, navigation, and telemetry has provided immense societal benefits including mobile broadband data, Internet of Things (IoT), mobile healthcare, and intelligent transportation systems. These and other applications including 5G and beyond wireless systems call for innovations that can circumvent the challenges of radio spectrum scarcity and interference and foster the growth of ubiquitous, high speed, low latency connectivity. Commercial applications like the above must operate in harmony with scientific uses such as research on radio astronomy, Earth and atmospheric sciences, and must not inhibit weather prediction, polar research, and other nationally vital activities, all of which are dependent upon access to the radio spectrum. The National Science Foundation (NSF) continues to support wireless spectrum research and the scientific uses of the electromagnetic spectrum through multiple programs that enable fast, accurate, dynamic coordination and usage of our limited spectrum resource. These programs have created an opportune ground to build and create a large center-based ecosystem for spectrum research, which is the target of this SII-Center program.

The Administration for Children and Families (ACF), Administration on Children, Youth and Families (ACYF), Family and Youth Services Bureau (FYSB) will award one cooperative agreement on a competitive basis for a period of three years to operate the Runaway and Homeless Youth National Communication System (NCS) Program. The NCS Program is a dedicated toll-free, U.S. national communication system that provides information, referral services, crisis intervention, prevention approaches, and communication services to vulnerable, at-risk, and runaway and homeless youth and their families or legal guardians. The purpose of the NCS is to a) prevent youth from running away and becoming homeless, and b) link youth with a family member or guardian, and/or an available resource that can provide and/or assist the youth in acquiring needed services. To fulfill the objectives of the legislation, the NCS must provide, among other services, a neutral and confidential channel of communication that is available on a 24-hours per day, seven days per week, basis throughout the United States so that youth contemplating running away and runaway and homeless youth may re-establish contact with their parents or legal guardians if possible. The NCS Program is also expected to work closely and collaboratively with FYSB to fulfill its mission as the federally funded communication system for runaway and homeless youth. A full description of services that will be required of the NCS grantee will provided in the published announcement.

Through this solicitation, OVC seeks to provide funding to organizations that demonstrate innovative strategies to create, expand, or enhance the use of technology on a national scale (or regional projects that can be replicated nationally) to improve responses, services, and access for victims of crime. OVC anticipates making up to three awards of up to $1.5 million each for a 24-month period of performance, to begin on October 1, 2020. OVC will conduct a pre-application webinar on Tuesday, March 31, 2020, from 1:00 to 2:00 p.m. e.t. Register at www.ovc.gov/grants/webinars.html. Apply by May 12, 2020.

This FOA invites applications to create an Artificial Intelligence and Technology Collaboratories for Aging Research Coordinating Center (AITCC), serving the needs of NIA and the NIAs Artificial Intelligence and Technology Collaboratories for Aging (AITC). The AITCC will serve as a hub for the AITC program and will facilitate and coordinate trans-AITC activities.

The Algorithms for Threat Detection (ATD) program supports research on new ways to use spatiotemporal datasets to develop quantitative models of human dynamics. The objectives include improved representation of complicated group dynamics and the development of algorithms that can process data in near real-time to accurately identify unusual events and forecast future threats indicated by those events.