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NSFDirectorate for Technology, Innovation, and Partnerships

ART Track 2: GROW: Georgetown Research & Innovation Translation (GRIT 2.0)

Active
Institution
Georgetown University, DC
Principal investigator
Tatiana Litvin-Vechnyak
Funding
$6.0M
Duration
2026–2030
Open portfolio

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Abstract

Universities generate discoveries with the potential to improve health, strengthen economic competitiveness, enhance national security, and address societal challenges. However, many promising innovations do not progress beyond the research stage because researchers often lack access to industry networks, market insights, translational expertise, and validation resources needed to advance technologies toward adoption and use. This project will strengthen institutional capacity to accelerate the translation of research discoveries into products, services, partnerships, and new ventures. Through expanded industry engagement, translational training, technology validation, and workforce development activities, the project will help researchers identify real-world applications, engage external stakeholders, and evaluate commercial opportunities earlier in the innovation process. The project will also create opportunities for students and postdoctoral researchers to participate in translational activities, preparing a workforce equipped to support technology-based economic growth and innovation. The project will implement an integrated, industry-informed research translation framework that combines technology assessment, market validation, workforce development, and commercialization support. Core activities will include establishing structured processes for evaluating both traditional and nontraditional intellectual property; deploying a network of industry, investor, and technical experts to provide market-informed feedback on emerging technologies; implementing a market-readiness sprint for researchers pursuing translational funding; and expanding interdisciplinary internship opportunities that engage students from science, business, law, and related fields in commercialization activities. The project will be informed by collaboration with Duke University, the mentor institution, which will provide guidance and best practices in translational research, commercialization, and innovation ecosystem development. Particular emphasis will be placed on strengthening institutional capabilities for evaluating and advancing physical sciences, software, artificial intelligence, data science, and other digital innovations, where commercialization pathways and support structures are often less developed than in traditional life science fields. The project will support Seed Translational Research Projects designed to generate technical, market, and partnership validation for early-stage technologies and will strengthen connections among researchers, industry partners, investors, and regional innovation ecosystem organizations. Expected outcomes include increased invention disclosures, greater participation in translational research activities, stronger industry partnerships, accelerated technology validation, increased licensing and startup activity, and enhanced institutional capacity to translate research discoveries into societal and economic impact. The ART Program, supported by the NSF TIP Directorate, seeks to advance the U.S. scientific and economic leadership by building capacity and increasing the number of robust translational research ecosystems in Institutions of Higher Education that span across the full geography of our nation. 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.

Research team

  • Tatiana Litvin-VechnyakPI
  • Jeffrey S UrbachCo-PI
  • Sandeep DahiyaCo-PI

LOADING MOONBASE SCORE

Directorate for Technology, Innovation, and Partnerships01002627DB NSF RESEARCH & RELATED ACTIVIT01002930DB NSF RESEARCH & RELATED ACTIVIT01002829DB NSF RESEARCH & RELATED ACTIVIT01002728DB NSF RESEARCH & RELATED ACTIVITART-Accelerating Rsrch Trnsltnuniversitiestranslationinsightsparticularstructuresimplementenhanceddirectoratefoundationdisclosures

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