Invitation, URI Speed Networking Event
AI, Quantum, and Computationally Enhanced Research & Innovation
Friday October 11, 2024, 9:30-noon
Galanti Lounge, 3rd Floor, URI Library
Center for Computational Research, ITS (Joan Peckham & Gaurav Khanna)
URI Innovation Lab (Jim McGwin)
College of Business, Business Analytics and AI (Drew Zhang)
URI Division of Research and Economic Development (Karen Markin)
PURPOSE: To support scholars at URI to respond to solicitations that increasingly request interdisciplinary, convergence1, use-inspired2, and data enabled research.
APPROACH: This event will provide a means for scholars of all disciplines with computational needs, and applied & theoretical data, quantum computing, mathematics, statistics and AI/analysis/management scholars to meet and explore interdisciplinary research collaborations that can result in publications, external funding and/or startups. URI scholars and students of all disciplines who are actively engaged in research and innovation are invited.
PROCESS: We will use a structured and timed speed dating approach that will give each scholar short segments of time to exchange their expertise, interests, and innovative ideas with other participants. Snack and beverages will be available upon arrival. At the end we will provide a grab and go lunch, but all will be welcome to stay and further discuss promising collaborations.
Registration by Friday, October 4, 2024 (So that we can order food): https://forms.gle/YHsFW3bRhhjgsw7B8
Questions? Contact jpeckham@uri.edu (Joan Peckham)
1 Convergence Research (https://beta.nsf.gov/funding/learn/research-types/learn-about-convergence-research): It is driven by a specific and compelling problem, whether that problem arises from deep scientific questions or pressing societal needs. It shows deep integration across disciplines. Convergence research intentionally brings together intellectually diverse researchers to develop effective ways of communicating across disciplines. As experts from different disciplines pursue a common research challenge, their knowledge, theories, methods, data and research communities increasingly intermingle.
2 Use-Inspired Research – From NSF solicitation on AI Institutes – NSF 22502 (https://www.nsf.gov/pubs/2022/nsf22502/nsf22502.htm): We use the phrase “use-inspired” rather than “applied” to emphasize that this solicitation seeks to support work that goes beyond merely applying known techniques and adds new knowledge and understanding in both foundational AI and use-inspired domains. Ideally there is a virtuous cycle between foundational and use-inspired research, where foundational results provide a starting point for use-inspired research, and the results from use-inspired research are generalized and made foundational.
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