Grants

NYC Department of Cultural Affairs

Creative Ammo, Inc.

Northern Westchester Ctr Arts

Creative Arts Poetry Café, Writers Fees + Promotion

NYC Department of Cultural Affairs

Creative Arts Workshops for Kids

NYC Department of Cultural Affairs

Creative Capital Foundation

Human Impacts Institute

The Creative Climate Communication Lab (C3 Lab) is a living lab for exploring, experimenting with, and understanding the impact of innovative, community-based engagement methods for driving climate action and community resilience.

Human Impacts Institute

The Creative Climate Communication Lab (C3 Lab) is a living lab for exploring, experimenting with, and understanding the impact of innovative, community-based engagement methods for driving climate action and community resilience.

RiseBoro Community Partnership Inc.

Creative Cultural Arts Program

NSF

Advanced manufacturing of electronics and mechanics has been widely identified as a key regional and national priority. The "making things" movement is harnessing the latest 2D and 3D digital fabrication technologies to creatively combine manufacturing and entrepreneurship. Regional employers have expressed the need for employees with creative technical design skills, entrepreneurial thinking skills, and the ability to produce precision systems. The goal of this project is to create a curriculum that teaches both design thinking and robotic manufacturing of devices and systems. This project will develop modules that will be offered through two-semester course offerings followed by an enhanced internship course for student-employer participation. The resulting educational pathway will provide students with the ability to design, troubleshoot, and prototype a common precision instrument. Students will fabricate a precision microsystem, acquiring skills such as disassembling, assembling, troubleshooting, and repairing using instructional resources, hands-on and design thinking information, and lab exercises. Students will gain experience in robotics, augmented reality, machine learning, and microelectronics and electronics systems topics. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the nation's economy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Creative Education Foundation

Creative Education Foundation is an active grantmaking foundation based in Kenmore, WA. Focus: education. Contact the foundation directly for current funding opportunities.

NYC Department of Cultural Affairs

Creative Minds NYC, Inc.

Creative Saskatchewan

Creative Saskatchewan supports the province's creative industries including film, music, publishing, and visual arts through grants and market development funding.

NYC Department of Cultural Affairs

Creative Time, Inc.

Cambridge Creative Commons

Creativity Club

Highland Falls

CREG Grant Highland Falls Dissolution Study

South Nyack

CREG Grant South Nyack Dissolution Study

Creighton Community Foundation

Creighton Community Foundation is an active grantmaking foundation based in Phoenix, AZ. Focus: philanthropy. Contact the foundation directly for current funding opportunities.

NSF

With support from the Centers of Research Excellence in Science and Technology (CREST) and the Engineering Research Centers (ERC), this project aims to facilitate a center for ultrawide bandgap semiconductor device materials and education. The project plans to combine semiconductor materials fabrication, processing, and characterization strategies along with modern Artificial Intelligence (AI). The researchers will focus on ultrawide bandgap (UWBG) semiconductors for next-generation devices operating at high power, high frequency, and under extreme conditions (temperature, radiation, corrosion, etc.). The center will also train and develop the next generation of technology leaders comprised of graduate and undergraduate students, and postdoctoral researchers. The project is part of a strategic goal of sustaining and developing research capacity to be a leading research institution in the UWBG semiconductor field within this decade. The aims of the research are interconnected via three subprojects. First, implement new fabrication, processing, and doping strategies to produce novel UWBG heterointerfaces. Second, develop new scanning probe microscopy based UWBG characterization techniques to interrogate UWBG heterointerfaces. And third, develop UWBG material aware AI-based models to investigate materials and heterostructures. UWBG semiconductors are an emerging class of materials for future technological demands of tremendously large power handling capacity and high switching speed for high power electronics. The Centers of Research Excellence in Science and Technology (CREST) program provides support to enhance the research capabilities of institutions through the establishment of centers that effectively integrate education and research. The Engineering Research Centers program supports collaborative, interdisciplinary research partnerships between universities and industry to advance engineered systems, drive technological innovation and cultivate a globally competitive engineering workforce for significant societal impact. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

With support from the Centers for Research Excellence in Science and Technology (CREST), this project aims to study sleep and internal circadian clocks that regulate sleep-wake cycles. These investigations are significant because lack of sleep has been associated with individuals whose occupations require shift-work. How circadian disruptions affect sleep is unknown. This project will identify how circadian disruptions affect the body. The goal of the project is to establish a world-class research center for circadian system biology. The research questions will focus on understanding how circadian rhythms adapt/resynchronize in response to frequently disrupted and ever-changing stimuli. The Center aims to: identify the neuronal network mechanisms by which light-dark signals are integrated by the circadian clock in the brain; probe the molecular mechanisms for the synchronization of circadian clocks outside of the brain; and determine the neurocircuitry underlying sleep. Research methods will include spatial transcriptomics, proteomics, computational neurobiology, and in vivo brain imaging. The project’s scope will engage collaborators to leverage additional cutting-edge technologies. The expected results are the identification of cellular and molecular mechanisms responsible for circadian disruptions. Results will be disseminated at meetings and in publications for the scientific and lay communities. Broader impacts include understanding and mitigating the adverse impact of circadian disruptions and training opportunities for students and faculty. The Center of Research excellence in Science and Technology (CREST) program provides support to enhance the research capability capabilities of institutions through the establishment of centers that effectively integrate education and research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

With support from the Centers of Research Excellence in Science and Technology (CREST), this project aims to establish the Center for Smart Manufacturing at California State Polytechnic University, Pomona. By harnessing the capabilities of artificial intelligence, the project will address critical challenges in efficiency, safety in human-robot collaboration, cybersecurity, and the shortage of advanced technical skills in modern manufacturing. The importance of this work lies in the need for manufacturing systems to evolve in order to meet growing demands for productivity, sustainability, and resilience. The project will unite researchers and industry experts to advance new methods and technologies that enhance predictability, optimize operations, and strengthen the reliability of U.S. manufacturing systems. The outcomes will contribute to new knowledge in smart manufacturing and provide advanced training opportunities for students, reinforcing the national workforce and supporting the long-term competitiveness of U.S. industry. The specific goals of the project are to develop and integrate four research thrusts within a cyber-physical manufacturing facility: (1) a digital twin-based factory with embedded artificial intelligence and two-way data exchange to improve safety and efficiency; (2) virtual and augmented reality approaches that improve human-system integration through adaptive training; (3) robotics and automation methods for autonomous manipulation in dynamic environments; and (4) artificial intelligence–enhanced cybersecurity protocols that strengthen communication standards and device authentication. The research scope will include both fundamental studies and applied solutions that enable secure, sustainable, and efficient manufacturing systems. Results will be disseminated through publications, workshops, conferences, and a dedicated center website, ensuring wide access to findings. The Centers of Research Excellence in Science and Technology (CREST) program provides support to enhance the research capabilities of institutions through the establishment of centers that effectively integrate education and research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

With support from the Centers of Research Excellence in Science and Technology (CREST) and the Engineering Research Centers (ERC), this project aims to create new materials and devices (bioderived thermoplastics, flexible hybrid recyclable electronics, sensors/actuators) of importance to numerous industries and federal agencies and tightly integrate research and education at Florida A&M University (FAMU). With artificial intelligence/machine learning (AI/ML) techniques to identify promising building block candidates, the project aims to use state-of-the-art synthesis, characterization and additive manufacturing techniques to yield biodegradable/recyclable novel structures and devices. CREST Phase II will enable long-term and multidisciplinary research at the cutting-edge of hybrid design and bioderived materials. Furthermore, CREST will contribute to developing FAMU capabilities while training the next generation of students in areas of national need. The scope of this CREST Phase II comprises the following subprojects – 1) High-throughput Discovery & Integration of Programmable Functional Polymer Nanocomposite Devices, 2) Bioderived, Recyclable, and Printable Polymer Matrices for Advanced Composites, and 3) Stimuli-Responsive Bio-Hybrid Soft Material Processing For 4D Fabrication and Microactuation. The goal is to develop novel functional bioderived thermoplastics and obtain structure-processing-function relationships useful to a wide variety of industrial processes. CREST Phase II aims to play a critical role in FAMU building to R1 status by increasing the number of Ph.D. graduates and to impact students through research collaborations and pedagogical practices. The Centers of Research Excellence in Science and Technology (CREST) program provides support to enhance the research capabilities of institutions through the establishment of centers that effectively integrate education and research. The Engineering Research Centers program supports collaborative, interdisciplinary research partnerships between universities and industry to advance engineered systems, drive technological innovation and cultivate a globally competitive engineering workforce for significant societal impact. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

City of Newberg

Crestview Drive Improvements

BCR Automotive Group dba Roesch Ford

Service Industry Machinery and Equipment and Supplies

NSF

The number of Internet-of-Things (IoT) devices has been increasing exponentially. By connecting billions of IoT devices, they will be able to support diverse applications, such as healthcare, energy management, education, social interaction, and public safety. The advancement of these applications, however, hinges on the development of efficient and secure communication techniques to facilitate interactions with heterogeneous IoT devices. This project aims to introduce analysis, models, and techniques to foster seamless collaboration among heterogeneous IoT devices while ensuring their secure communication. The project should enrich the scientific knowledge of communication and security theory, signal processing, and networking. Furthermore, it has the potential to address the grand challenges in crowded wireless channels to support ubiquitous connectivity in heterogeneous IoT networks. Additionally, this project will contribute to the cross-disciplinary development of students at Saint Louis University and the establishment of graduate-level courses on IoT and communication theory. The objective of this project is to exploit, model, and leverage hidden features in heterogeneous IoT devices for cross-layer design, thereby improving the performance of IoT networks and enabling secure asymmetric communication across heterogeneous IoT devices with different communication protocols. The project is structured around two main thrusts. The first thrust introduces models and optimization techniques aimed at improving network performance across heterogeneous IoT devices by reducing latency and overhead, as well as enhancing throughput and reliability. The second thrust focuses on exploring and exploiting the unique and hidden physical-layer features of heterogeneous IoT devices, including spatial distribution of signal distortion and errors, to enable secure cross-IoT communication. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

Within the last 15 years, permissionless, decentralized electronic cash systems based on a public consensus mechanism, such as Bitcoin, have emerged as credible tools for efficient cross-border payments, financial inclusion and debasement protection. While payment channel networks (PCNs) such as the Lightning network help to overcome their inherent limitations with respect to payment throughput and transaction speed, the reliability of such off-chain payments is not guaranteed, especially for participating individuals with limited abilities to allocate large capital amounts to establish payment channels. So-called multipart payments have the potential to ensure reliable, cheap payments within PCNs, but to reach their full potential, require the solution of non-standard optimization problems which are challenging for currently available optimization algorithms and solvers. This project aims to fill this gap and develop novel optimization algorithms suitable for such problems, and to provide scalable implementations via an open-source software toolbox. The resulting algorithms will also of useful for urban planners, in particular in the context of public transportation and road systems. For such urban planning applications, designs can be improved by solving related optimization problems whose formulations jointly model commuter goals, capacity constraints and economies of scale. The research project involves the mentoring of a graduate student as well as the development of new course materials on the technology of digital asset systems into existing course curricula. As a first goal, the project aims to develop prototypes of iterative optimization algorithms for capacitated and uncapacitated minimum-cost flow problems with non-convex objectives based on continuous optimization and the framework of iteratively reweighted least squares, building on a new generation of robust Laplacian linear system solvers to solve the associated subproblems. Subsequently, the project intends to generalize these algorithms to problems involving multicommodity flows and to develop scalable software implementations that are adapted to the specific necessities and challenges within payment channel networks and transportation networks. A complementary research thrust within the project is the theoretical convergence analysis of the resulting algorithms, which will shed light on their performance guarantees and limitations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.