OARS funding Computer

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. At the same time, broad acceptance of large-scale deployments of AI systems relies critically on their trustworthiness which, in turn, depends upon the collective ability to ensure, assess, and ultimately demonstrate the fairness, transparency, explainability, and accountability of such systems. Importantly, the beneficial effects of AI systems should be broadly available across all segments of society. 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, validation of fairness, and considerations of inclusivity. 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.

The objective of this Announcement is to enhance the reliability and resilience of the energy infrastructure through innovative research, development and demonstration cybersecurity solutions. This Announcement includes three topic areas. Topic Area 1 is Real Time Intrusion for Energy Delivery Control Systems. Topic Area 2 is Self Healing Energy Delivery Control Systems. Topic Area 3 is Innovative Technologies that Enhance Cybersecurity in the Energy Sector.

The Synergistic Population and Data Science Award mechanism supports multi-institutional partnerships that will leverage existing prostate cancer patient datasets or cohorts to answer questions that will make a significant impact in addressing the FY19 PCRP Overarching Challenges. Thus, applications must be responsive to at least one of the FY19 PCRP Overarching Challenges. The award is intended to support both the development of infrastructure to facilitate access to multiple datasets/cohorts by a team of investigators, as well as conducting hypothesis-based studies utilizing the multi-institutional datasets. To qualify for this mechanism, a minimum of three institutions and three well-annotated patient datasets/cohorts is required. Dataset Coordination: Central to the pursuit of the hypothesis proposed in the application is the development of the infrastructure to facilitate multi-institutional access to the identified datasets/cohorts. The application must describe the key elements that will need to be in place in order to facilitate the multi-institution collaboration, including: * Administrative and management plans for decision-making and allocation of resources * Description of the dataset logistics, including storage, how data will be shared among PIs/institutions, and plans for data harmonization * Description of key members and roles of the multi-institutional research team * Communication plans among the research team members to discuss research progress and results * Regulatory plan, including coordination of local Institutional Review Board (IRB) approvals * Data security and integrity measures * Intellectual property plan * Plan for disseminating information and distributing data to the prostate cancer research community

A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications, healthcare informatics and business analytics.

The Intellectual Property Enforcement Program (IPEP), administered by BJA, is designed to provide national support and improve the capacity of state, local, and tribal criminal justice systems to address IP enforcement, including prosecution, prevention, training, and technical assistance. Awards will be made by BJA to support law enforcement agencies in coordinating the goals, objectives, and activities of their IP enforcement task forces in close collaboration with the relevant state, local, tribal, and federal agencies, to include local U.S. Attorney's Offices (USAOs). The improved coordination of IP enforcement efforts among federal, state, and local authorities is a central goal of the Strategic Plan and is of primary importance to DOJ. As a result, projects funded under this solicitation must align with the mission of the DOJ IP Task Force, and establish and/or enhance state and local IP enforcement task forces that include relevant law enforcement agencies and federal agencies (to include, where appropriate, local offices of the Federal Bureau of Investigation [FBI], U.S. Immigration and Customs Enforcement's Homeland Security Investigation [ICE HSI], and U.S. Attorneys.

BJA’s Student Computer Forensics and Digital Evidence Educational Opportunities Program is an innovative new program that seeks to partner with an institution of higher education to further educational opportunities for students in the fields of computer forensics and digital evidence. This practical and academic program will better prepare students for employment within federal, state, local, territorial, and tribal law enforcement agencies that are charged with the prevention, investigation, and response to economic, cyber, and high-tech crimes.

The NSF Directorate for Computer and Information Science and Engineering (CISE) seeks to award grants intended to support research independence among early-career academicians who specifically lack access to adequate organizational or other resources. It is expected that funds obtained through this program will be used to support untenured faculty or research scientists (or equivalent) in their first three years in a primary academic position after the PhD, but not more than five years after completion of their PhD. Applicants for this program may not yet have received any other grants or contracts in the PI role from any department, agency, or institution of the federal government, including from the CAREER program or any other program, post-PhD, regardless of the size of the grant or contract, with certain exceptions as noted below. Serving as co-PI, Senior Personnel, Postdoctoral Fellow, or other Fellow does not count against this eligibility rule. Importantly, the CRII program seeks to provide essential resources to enable early-career PIs to launch their research careers. For the purposes of this program, CISE defines "essential resources" as those that (a) the PI does not otherwise have, including through organizational or other funding; and (b) are critical for the PI to conduct early-career research that will enable research independence. In particular, this program is not appropriate for PIs who already have access to resources to conduct any early-career research.

The National Geographic Society is accepting applications for its Participatory Science program, which supports the development or innovative use of data-driven, technology-powered tools that increase the understanding, preservation, and protection of our planet. Applicants should propose tools that support citizen science work, particularly data collection or data analysis, in ways that create learning experience for citizen scientists, including students. Priority will be given to research, education, and technology projects that create and execute new digital applications, transform existing applications and products, or use current technologies to do one or more of the following: teach students and other citizen scientists about the planet using experiential, crowdsourced technology; encourage individuals who engage with these technologies and projects to build the attitudes, skills, and knowledge necessary to become stewards of the planet and contribute to solving real-world issues; and generate data and/or develop open-source technologies that contribute to scientific inquiry and advance our understanding of the planet.

Co-founded in New York City by Jim and Marilyn Simons, the Simons Foundation works to advance the frontiers of research in mathematics and the basic sciences. To that end, the foundation is accepting applications for its Targeted Grants in Mathematics and Physical Sciences (MPS) program, which supports projects of exceptional promise and scientific importance in theoretical mathematics, physics, and computer science with flexible funding for up to five years. Although the emphasis of the program is theory, projects with some experimental components may be considered.   Principal investigators and co-investigators must have a PhD and a tenure-track or tenured position at an established U.S. or foreign public or private educational institution or standalone research center. There are no citizenship or department requirements for principal investigators.

Society's overwhelming reliance on this complex cyberspace, however, has exposed its fragility and vulnerabilities that defy existing cyber-defense measures; corporations, agencies, national infrastructure and individuals continue to suffer cyber-attacks. Achieving a truly secure cyberspace requires addressing both challenging scientific and engineering problems involving many components of a system, and vulnerabilities that stem from human behaviors and choices. Examining the fundamentals of security and privacy as a multidisciplinary subject can lead to fundamentally new ways to design, build and operate cyber systems, protect existing infrastructure, and motivate and educate individuals about cybersecurity. The Secure and Trustworthy Cyberspace (SaTC) program welcomes proposals that address cybersecurity and privacy, and draw on expertise in one or more of these areas: computing, communication and information sciences; engineering; economics; education; mathematics; statistics; and social and behavioral sciences. Proposals that advance the field of cybersecurity and privacy within a single discipline or interdisciplinary efforts that span multiple disciplines are both encouraged.

An initiative of the Open Technology Fund, the Internet Freedom Fund strives to build the capacity of individuals, organizations, and companies working to advance technology-centered efforts designed to strengthen Internet freedom and promote human rights by circumventing repressive censorship and surveillance, improving related digital security capabilities, and contributing to the overall health of the Internet. To that end, ITF invites applications focused on creating new open source circumvention technologies that fill a current need of target users; improve the security, usability, and adaptability of existing open source Internet freedom technologies; and/or provide new or deeper insight into the challenges of front-line communities that ultimately contribute to the improvement of technological solutions .The fund also supports applied research; research that focuses on real-time monitoring and analysis of both technical and political threats to Internet freedom; new content redistribution methods able to reintroduce content behind firewalls; and next-generation tools that move beyond traditional "cat-and-mouse" circumvention techniques.

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. At the same time, broad acceptance of large-scale deployments of AI systems relies critically on their trustworthiness which, in turn, depends upon the collective ability to ensure, assess, and ultimately demonstrate the fairness, transparency, explainability, and accountability of such systems. Importantly, the beneficial effects of AI systems should be broadly available across all segments of society. 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, validation of fairness, and considerations of inclusivity. 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.

The Directorate for Computer and Information Science and Engineering (CISE) has established the Expeditions in Computing (Expeditions) program to provide the CISE research and education community with the opportunity to pursue ambitious, fundamental research agendas that promise to define the future of computing and information. In planning Expeditions projects, investigators are encouraged to come together within or across departments or institutions to combine their creative talents in the identification of compelling, transformative research agendas that promise disruptive innovations in computer and information science and engineering for many years to come

The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) announces the opportunity for potential performers to meet with a DSO program manager (PM) to discuss mutual research interests. These meetings will be held in conjunction with the Discover DSO Day event scheduled for June 18-19, 2019 in Arlington, Virginia.

The ICAC Task Force National Training Program supports a national network of 61 multiagency, multijurisdictional task forces engaged in investigation, forensics examinations, and prosecutions related to technology-facilitated child sexual exploitation. The funding will assist in development and delivery of content by SMEs, provide comprehensive array of trainings to the growing number of ICAC task forces in the areas of investigations, prosecutions, digital forensic, community outreach, and capacity building. This solicitation will include four categories as follows: Category 1: Entry Level and Core Training Category 2: Specialized Training on Issues, Tools and Technology Category 3: Officer Wellness

The Public Affairs Sections of the U.S. Consulate General Karachi (PAS Karachi) is pleased to announce an open competition for assistance awards through this Notice of Funding Opportunity (NOFO), contingent on funding availability, through the Public Diplomacy Grants Program. The projects set forth in this NOFO support individual and institutional capacity-building in STEM entrepreneurship. Two (2) different projects are described in this NOFO. Organizations may submit one proposal for each project, but no more than one proposal per project. Project 1: Entrepreneurship and Software Engineering: To develop and leverage entrepreneurial skills of women in and around Hyderabad, Sukkur, Khairpur, and Larkana, particularly in the textile industry. Project 2: STEM Hackathon: A STEM hackathon for female programmers in Karachi, Hyderabad, and Quetta, to engage more girls in STEM-related fields; to help women in STEM-related fields to find and connect with mentors; and to identify solutions to career or education-related challenges that women in STEM fields face.

The U.S. Department of State, Bureau of Democracy, Human Rights, and Labor (DRL) announces an open competition for organizations interested in submitting applications for programs that promote Internet freedom in Ukraine. In support of the National Cyber Strategy for the United State of America, DRL's goal is to promote an open, interoperable, reliable, and secure Internet by promoting human rights, fundamental freedoms, and the free flow of information online.

The need to process large data sets arising in many practical problems require real-time learning from data streams makes high-performance hardware necessary, and yet the very nature of these problems, along with currently known algorithms for addressing them, imposes significant hardware challenges. Current versions of deep-learning algorithms operate by using millions of parameters whose optimal values need to be determined for good performance in real time on high-performance hardware. Conversely, the availability of fast hardware implementations can enable fuller use of Bayesian techniques, attractive for their ability to quantify prediction uncertainty and thus give estimates of reliability and prediction breakdown. The abilities of ML systems to self-assess for reliability and predict their own breakdowns (and also recover without significant ill effects) constitute critical areas for algorithm development as autonomous systems become widely deployed in both decision support and embodied AI agents. Only with attention to these challenges can we construct systems that are robust when they encounter novel situations or degradation and failure of sensors.

A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications,healthcare informatics and business analytics. A salient feature of these emerging domains is the large and continuously streaming data sets that these applications generate, which must be processed efficiently enough to support real-time learning and decision making based on these data. This challenge requires novel hardware techniques and machine-learning architectures.This solicitation seeks to lay the foundation for next-generation co-design of RTML algorithms and hardware, with the principal focus on developing novel hardware architectures and learning algorithms in which all stages of training (including incremental training, hyperparameter estimation, and deployment) can be performed in real time. The National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA) are teaming up through this Real-Time Machine Learning (RTML) program to explore high-performance, energy-efficient hardware and machine-learning architectures that can learn from a continuous stream of new data in real time, through opportunities for post-award collaboration between researchers supported by DARPA and NSF.

In selecting projects for funding, the Foundation seeks proposals for original initiatives led by outstanding individuals or teams.  We are interested in projects that have a high expected return to society, exhibit a high degree of methodological rigor, and for which funding from the private sector, government, or other foundations is not yet widely available.