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Find similar grantsDiscovering the Future of AI grants program (AI + Education track) is sponsored by University of Pennsylvania (PennAI). This program provides faculty with resources to pursue paradigm-shifting research and education in AI and its applications.
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Discovering the Future of AI | Penn AI Discovering the Future of AI Penn AI is pleased to announce the first four awardees for the Discovering the Future of AI awards. Fifty-four competitive applications were submitted in response to the request for proposals, representing creative and bold ideas in research and education across Penn’s schools.
In addition to the four awards totaling $450,000, an additional 31 faculty applicants representing eleven schools received awards for high performance computing needs supported by the Penn Advanced Research Computing Center (PARCC) for an estimated value of $852,000, bringing the total support to $1. 3 million.
Access to high-performance computing enables Penn researchers to run state-of-the-art AI models, analyze far larger datasets, and pursue bold, high-risk ideas without financial constraints. The Discovering the Future award is designed to catalyze high-risk, high-reward research and education at the intersection of artificial intelligence and domain scholarship for the benefit of society.
We congratulate the following four awardees: CASPER4D: Computer Assisted Surgical Performance Evaluation via Reconstruction Assistant Professor of Surgery, Perelman School of Medicine (in collaboration with School of Engineering and Applied Sciences) CASPER4D is a collaborative research project using AI to reconstruct four-dimensional surgical environments from standard video to assess skill, predict risk, and improve patient outcomes.
The Penn AI Pedagogy Initiative: Building Capacity for Meaningful and Responsible Adoption at Scale Associate Professor, Graduate School of Education (in collaboration with School of Arts & Sciences) The Penn AI Pedagogy Initiative supports faculty and students in co-designing AI-enhanced teaching practices, building a scalable framework for responsible AI adoption in education.
Molecule 3D Structure Informed Science Agentic LLM Presidential Associate Professor, Perelman School of Medicine (Microbiology) (in collaboration with School of Engineering and Applied Sciences) ApexMol will integrate language and 3D molecular structure to enable AI systems to reason about and design new biomolecules, accelerating discovery.
EchoMFM: A Multimodal Foundation Model for Automated Clinical Interpretation of Echocardiograms Professor, Perelman School of Medicine (Cardiovascular Medicine) EchoMFM will integrate imaging, EHR, reports, ECG, and MRI data to generate draft clinical interpretations and improve diagnostic efficiency.
The Discovering the Future of AI grants program provides faculty with critical resources to pursue paradigm-shifting research and education in AI and its applications. The goal is to foster synergies that pair the latest advances in AI with novel applications across disciplines to unlock new frontiers of discovery.
This call will provide funding for one year (see below for details) but proposals that lead to successful outcomes, especially ones with broader impact at Penn, will be eligible for additional funding in subsequent years. A key goal of this program is to foster genuine collaboration between AI experts and domain experts. We strongly encourage proposals from all disciplines and schools.
Proposals led jointly by two Co-Principal Investigators (Co-PIs) from different schools are particularly encouraged: one should be a core AI/ML faculty member, and the other a faculty expert in the relevant application domain.
Proposals must be aligned with one or more of the strategic research thrusts of PennAI: AI Foundations: Understanding the fundamental principles behind existing AI algorithms and developing the next generation of AI algorithms. AI + Business: Exploring how AI will reshape industries, economies, and the future of work itself.
AI + Education : Developing educational programs or innovative in-class teaching (undergraduate or graduate) that leverage AI tools to transform the educational experience and/or advance Penn’s leadership in AI education. AI + Health: Revolutionizing healthcare through AI-driven diagnostics, personalized medicine, computational biology, and optimization of clinical care.
AI + Science: Applying AI to accelerate discovery in the natural sciences, from discovering new materials and modeling climate change to unraveling the mysteries of the human mind. AI + Society: Investigating the societal impact of AI, building trustworthy and ethical algorithms, or using AI to create new knowledge in the humanities and social sciences.
Examples of support include, but are not limited to: Funding for the development of novel AI models and experiments. Funding for acquiring or creating unique datasets necessary for transformative research. Funding for graduate students or postdoctoral fellows for complex data analysis and model development.
Applied research that tackles real-world problems, or develops new products, technologies, or policies, especially research that incorporates community partnerships. Funding for the development of educational programs or innovative in-class teaching. Limitation: One (1) application per faculty member.
For any sponsored research projects, the applicant must be eligible to serve as Principal Investigator for the project, unless otherwise noted in this opportunity. Please see Penn’s PI Eligibility requirements to ensure you are eligible. For any educational program or course, applicants must provide a detailed explanation of how AI will enhance the course, impact students, and advance Penn’s leadership in AI/ML education.
An unrestricted research award of up to $200,000 for one (1) year. Awards are for direct costs only. Internal Selection Process: The Office of the Vice Provost for Research and the Penn AI Council invite Penn Faculty to submit one (1) application for consideration.
Applications must include the following: Cover Page (InfoReady will autogenerate) including: Candidate’s name, academic rank, department, email address, phone number, and campus address. Research projects specify one of the following categories (refer to the Penn AI website for details at: https://ai. upenn.
edu/ai-penn) Abstract (maximum 1 page) Project description: ( maximum 4 pages, not including references; single-spaced, 12-point font with one-inch margins ) All projects must identify a second audience outside of the academic community. Who are the primary and secondary audiences of this project, and how will the research or new educational methods benefit them?
Brief Project Budget (maximum 1 page) Course syllabus: ( Optional, if not relevant to proposal ) Provide the course syllabus and/or a detailed explanation of how the AI educational funding will change the course, impact students, or broaden Penn as the leader in AI/ML education. Curriculum Vitae (CV) (maximum 2 pages)
Based on current listing details, eligibility includes: Faculty position at the University of Pennsylvania, eligible to serve as Principal Investigator for sponsored research projects. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Up to $200,000 for one year Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
Note: Each funding opportunity description is a synopsis of information in the Federal Register application notice. For specific information about eligibility, please see the official application notice. The official version of this document is the document published in the Federal Register. Free Internet access to the official edition of the Federal Register and the Code of Federal Regulations is available on GPO Access at: http://www.access.gpo.gov/nara/index.html. Please review the official application notice for pre-application and application requirements, application submission information, performance measures, priorities and program contact information. Purpose of Program: The purpose of this program is to stimulate technological innovation in the private sector, strengthen the role of small business in meeting Federal research or research and development (R/R&D) needs, increase the commercial application of the U.S. Department of Education (Department) supported research results, and improve the return on investment from federally funded research for economic and social benefits to the Nation. Catalog of Federal Domestic Assistance (CFDA) Number: 84.133S-1. If you choose to submit your application electronically, you must use the Governmentwide Grants.gov Apply site at http://www.Grants.gov. Through this site, you will be able to download a copy of the application package, complete it offline, and then upload and submit your application. You may not e-mail an electronic copy of a grant application to us. You may access the electronic grant application for the SBIR Program at: http://www.Grants.gov. You must search for the downloadable application package for this competition by the CFDA number. Do not include the CFDA number's alpha suffix in your search (e.g. , search for 84.133, not 84.133S). The telephone number for the Grants.gov Helpdesk is 1-800-518-4726 or e-mail: support@grants.gov. Funding Opportunity Number: ED-GRANTS-090908-001. Assistance Listing: 84.133. Funding Instrument: G. Category: ED. Award Amount: Up to $75K per award.
The National Leadership Grants for Libraries Program (NLG-L) supports projects that address critical needs of the library and archives fields and have the potential to advance practice and strengthen library and archival services for the American public. Successful proposals will generate results such as new models, tools, research findings, services, practices, and/or alliances that can be widely used, adapted, scaled, or replicated to extend and leverage the benefits of federal investment. Applications to IMLS should both advance knowledge and understanding and ensure that the federal investment made generates benefits to society. Specifically, the goals for this program are to generate projects of far-reaching impact that: • Build the workforce and institutional capacity for managing the national information infrastructure and serving the information and education needs of the public. • Build the capacity of libraries and archives to lead and contribute to efforts that improve community well-being and strengthen civic engagement. • Improve the ability of libraries and archives to provide broad access to and use of information and collections with emphasis on collaboration to avoid duplication and maximize reach. • Strengthen the ability of libraries to provide services to affected communities in the event of an emergency or disaster. • Strengthen the ability of libraries, archives, and museums to work collaboratively for the benefit of the communities they serve. Throughout its work, IMLS places importance on diversity, equity, and inclusion. This may be reflected in an IMLS-funded project in a wide range of ways, including efforts to serve individuals of diverse geographic, cultural, and socioeconomic backgrounds; individuals with disabilities; individuals with limited functional literacy or information skills; individuals having difficulty using a library or museum; and underserved urban and rural communities, including children from families with incomes below the poverty line. Application Process: The application process for the NLG-L program has two phases; applicants must begin by applying for Phase I. For Phase I, all applicants must submit Preliminary Proposals by the September 20th deadline listed for this Notice of Funding Opportunity. For Phase II, only selected applicants will be invited to submit Full Proposals, and only those Invited Full Proposals will be considered for funding. Invited Full Proposals will be due March 20, 2024. Funding Opportunity Number: NLG-LIBRARIES-FY24. Assistance Listing: 45.312. Funding Instrument: G. Category: AR,HU. Award Amount: $50K – $1M per award.
The California Department of Education (CDE) Early Education Division is making approximately .7 million available to expand California State Preschool Program (CSPP) services statewide, appropriated under the 2021 Budget Act. Eligible applicants are local educational agencies (LEAs), including school districts, county offices of education, community college districts, and direct-funded charter schools—both current CSPP contractors and new applicants. Funding supports full-day/full-year or part-day/part-year preschool services for income-eligible children beginning in FY 2024–25. Awards are allocated by county based on Local Planning Council priority areas and application scores, with redistribution provisions if county allocations are underutilized.