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Explore the transformative potential of generative AI in university-research administration. As universities strive to enhance research capabilities and support a culture of innovation, the need for efficient and effective management of sponsored programs has become paramount. This presentation will share lessons from deploying a sponsored programs’ Large Language Model Chatbot and how it optimizes research administration operations and unlocks opportunities. By harnessing the power of GenAI, a university office of sponsored programs chatbot can develop training materials, policies and SOPs. It can offer immediate support and guidance by analyzing queries and providing real-time responses, empowering staff members to overcome challenges and reducing time on tasks. It can enhance productivity and job satisfaction. An OSP Chat will allow research administrators to focus on higher-value activities, such as strategic planning, relationship building and facilitating research collaboration resulting in improved operational effectiveness and increased capacity to support research excellence. This improves the quality of research administration services. This presentation will highlight the collaboration of AI experts, research administrators and stakeholders to tailor LLM to the research administration's needs, maximizing staff benefits and optimizing research support.
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Generating Reliable Collaboration Data: A Proof-of-Concept Project Using Research Administration Data
Central administration at Rutgers University requested help from the Office for Research to develop a proof-of-concept tool to count collaborations between faculty, departments, schools and chancellor units across the university. This presentation will discuss how the Data, Analytics and Business Intelligence team focused on research administration and research output data to define a “collaboration,” structure available data, create interactive visualizations and allow end users to customize the level of detail displayed. This presentation will begin by discussing the importance of generating reliable collaboration data in a university setting including use cases for the data. It will then describe the dataset that was used for the proof-of-concept project and discuss why these sources were important. Finally, the presentation will discuss future development goals and collaborators for the collaboration project.
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- Award ID(s):
- 2324388
- PAR ID:
- 10566921
- Publisher / Repository:
- University of Kentucky Libraries
- Date Published:
- Subject(s) / Keyword(s):
- FOS: Computer and information sciences
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Proceeding:
- https://doi.org/10.13023/3ZF7-RG83
