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SUMMARY:AI Research Seed Grants Informational Session
DTSTART:20260915T160000Z
DTEND:20260915T170000Z
DTSTAMP:20260827T215402Z
LAST-MODIFIED:20260827T215508Z
SEQUENCE:0
LOCATION:Danforth Unviersity Center (DUC) 276
DESCRIPTION:\nJoin the WashU Research Development Office to learn more about the three research seed grants offered to WashU faculty investigators. \n\n\n\nThe FY 2027 program encourages applications from innovative\, interdisciplinary research projects and teams that meaningfully integrate Artificial Intelligence (AI) into their research. The aim is to catalyze cross-school\, interdisciplinary collaborations to advance discovery\, enhance research capabilities\, and address complex societal challenges by leveraging AI as a transformative\, enabling tool. By supporting work that integrates AI thoughtfully and responsibly\, this initiative aims to catalyze research that is both innovative within its field and competitive for external support.\n\n\n\nOffice hours are held from 10 - 11 a.m. before the informational session.\n\n\n\n\nRegister to attend\n\n\n\n\nThe examples below are illustrative and not exhaustive:\n\n\n\n\nAI as an Enabler of Discovery (“X + AI”): Work that integrates AI to generate new knowledge\, augment existing methods\, and foster cross-disciplinary collaboration between computational and domain experts.\n\n\n\nAI-Augmented Research Workflows: Work that uses AI to enhance research processes\, including data analysis\, modeling\, simulation\, and hypothesis generation\, as well as the development of scalable\, AIassisted approaches.\n\n\n\nData\, Infrastructure\, and AI Readiness: Work that advances the development or use of datasets\, data pipelines\, and computational tools that enable effective and responsible use of AI.\n\n\n\nResponsible\, Ethical\, and Human-Centered AI: Work that addresses fairness\, bias\, transparency\, explainability\, governance\, and the broader ethical\, legal\, and societal implications of AI\, including humanAI interaction and AI-enabled decision making.\n\n\n\nTranslation\, Practice\, and Real-World Impact: Work that advances AI-enabled applications in applied or practice-based settings including pilot projects\, prototypes\, and implementation-oriented research.\n\n\n\nAI for Complex and Societal Challenges: Work that applies AI to pressing challenges such as resilient ecosystems\, health and wellbeing\, and social and economic systems\, as well as other emerging areas of inquiry.\n\n
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