OARS funding Computer

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.

Submit an application if you are a successful top-rank junior researcher from abroad, only completed your doctorate with distinction in the last six years, and have published work in prestigious international journals or publishing houses. The Sofja Kovalevskaja Award allows you to spend five years building up a working group and working on a high-profile, innovative research project of your own choice at a research institution of your own choice in Germany.

The ACI is a DoD-sponsored computing systems research program initiated by the NSA and the Combat Capabilities Development Command/Army Research Laboratory/ARO. It focuses on areas of strategic importance to U.S. national security policy. It seeks to increase the Department's intellectual capital in computing systems and improve its ability to address future challenges and build bridges between the Department and the computing research community. ACI brings together universities, research institutions, companies, and individual scholars and supports multidisciplinary and cross-institutional projects addressing specific topic areas determined by the Department of Defense. The ACI aims to promote research in specific areas of computing systems and to promote a candid and constructive relationship between DoD and the computing research community.

SC hereby invites grant applications for support under the Early Career Research Program in the following program areas: Advanced Scientific Computing Research (ASCR); Biological and Environmental Research (BER); Basic Energy Sciences (BES), Fusion Energy Sciences (FES); High Energy Physics (HEP), and Nuclear Physics (NP). The purpose of this program is to support the development of individual research programs of outstanding scientists early in their careers and to stimulate research careers in the areas supported by SC.

This notice solicits applications to support a Telehealth Center of Excellence. The primary purpose of this program is to examine the efficacy of telehealth[1] services in rural and urban areas. The Telehealth Center of Excellence will be located in a public academic medical center that: Has a successful telehealth program with a high annual volume of telehealth visits; Has an established reimbursement structure that allows telehealth services to be financially self-sustaining; and Has established programs that provide telehealth services in medically underserved areas with high chronic disease prevalence and high poverty rates. The Telehealth Center of Excellence will serve as a national clearinghouse for telehealth research and resources, including technical assistance. To achieve that goal, the Telehealth Center of Excellence should have substantial experience operating a telehealth program that offers a broad range of clinical services and has experience demonstrating how their efforts have improved access to care and enhanced health outcomes for their patients. [1] The Office for the Advancement of Telehealth defines Telehealth as the use of electronic information and telecommunication technologies to support and promote long-distance clinical health care, patient and professional health-related education, public health, and health administration. Technologies include video conferencing, the internet, store-and-forward imaging, streaming media, and terrestrial and wireless communications.

The Space/Time Analysis for Cybersecurity (STAC) program seeks to enable analysts to identify algorithmic resource usage vulnerabilities in software at levels of scale and speed great enough to support a methodical search for them in the software upon which the U.S. government, military, and economy depend. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice. See the full DARPA-BAA-14-60 document attached.

The purpose of this Funding Opportunity Announcement (FOA) is to solicit revisions (competitive supplements) to add a Big Data Science track to active T15 institutional training grants for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with biomedical Big Data in the biomedical sciences (see definition under Funding Opportunity Description). This proposed training initiative should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical data.

In recognition of the importance of research to the advancement of librarianship and information science, OCLC and ALISE promote independent research that helps integrate new technologies that offer innovative approaches and contributes to a better understanding of the information environment and user expectations and behaviors. Research related (but not limited) to the following areas is encouraged: Impact of digital technology on libraries, museums, and archives Social media, learning, and information-seeking behavior New developments in knowledge organization (metadata, social tagging, linked data, etc.)

The Allen Distinguished Investigator (ADI) Program seeks to fund a select group of investigators to pursue new, pioneering research in academic settings that, collectively, 'move the needle' towards answering broad scientific questions. The most promising proposals will incorporate novel, creative, and ambitious approaches. For this reason, the program is especially interested in proposals that are unlikely to receive funding from traditional governmental sources.   For 2014, the Foundation will make awards in two areas: Life Sciences and Artificial Intelligence (AI). (Information regarding the ADI for Life Sciences will be announced at a later date.)   We are pleased to announce the Artificial Intelligence awards will focus on three fundamental topics:   Machine Reading Diagram Interpretation Spatial and Temporal Reasoning

This Funding Opportunity Announcement (FOA) solicits applications from single institutions, or consortia of institutions, to participate in a network of research groups developing computational models of immunity to infectious diseases other than HIV/AIDS. Applications are sought to develop, refine and validate computational models of immune responses (1) during or following infection, and/or (2) before and after vaccination against an infectious disease, through an iterative approach involving computational studies and immunological experimentation. The main goal of this FOA is to advance our understanding of the complex immune mechanisms triggered by infection and/or vaccination through the development and application of computational models of immunity, coupled with immunological experimentation to validate and improve the utility and robustness of the computational models.Another goal of this FOA is to make the computational models and data developed under this initiative readily available to the broader research community for further refinement or direct use in biological experimentation. This program will also support pilot projects, workshops, and symposia to foster the use of computational models of immunity by the broader research community.

The goals of the Resilient Interdependent Infrastructure Processes and Systems (RIPS) solicitation are (1) to foster an interdisciplinary research community that discovers new knowledge for the design and operation of infrastructures as processes and services  (2) to enhance the understanding and design of interdependent critical infrastructure systems (ICIs) and processes that provide essential goods and services despite disruptions and failures from any cause, natural, technological, or malicious, and (3) to create the knowledge for innovation in ICIs to advance society with new goods and services. The objectives of this solicitation are: Create theoretical frameworks and multidisciplinary computational models of interdependent infrastructure systems, processes and services, capable of analytical prediction of complex behaviors, in response to system and policy changes. Synthesize new approaches to increase resilience, interoperations, performance, and readiness in ICIs. Understand organizational, social, psychological, legal, political and economic obstacles to improving ICI's, and identifying strategies for overcoming those obstacles. The RIPS solicitation seeks proposals with transformative ideas that will ensure ICIs services are effective, efficient, dependable, adaptable, resilient, safe, and secure.  Successful proposals are expected to study multiple infrastructures focusing on them as interdependent systems that deliver services, enabling a new interdisciplinary paradigm in infrastructure research.  Proposals that do not broadly integrate across the cyber-physical, engineering and social, behavioral and economic (SBE) sciences may be returned without review.