Exploring Generative AI and OIEx’s Curated Data to Strengthen Discovery
Universities increasingly recognize interdisciplinary collaboration as essential for addressing complex challenges. Yet forging effective partnerships across academia, industry, and government often proves difficult, hindered by siloed organizational structures and language barriers.
Simply convening potential collaborators is rarely enough. Successful partnerships depend on clear communication and shared understanding. Industry professionals frequently describe emerging technologies using terminology unfamiliar to academics, who tend to reference more traditional disciplinary frameworks. This linguistic gap can frustrate discovery when industry seeks academic expertise.
To illustrate the point, Tim Cain of OIEx noted: “From aviation pioneers Orville and Wilbur Wright to early aerospace trailblazers Neil Armstrong and John Glenn, Ohio has a longstanding connection with aviation and aerospace innovation. Today, as investment in advanced air mobility technologies accelerates, Ohio stakeholders are exploring how OIEx’s access to academic expertise and shareable assets can help identify, connect, and convene collaborators more quickly.
“Industry professionals searching for expertise in areas such as vertiports, low-altitude traffic management, and navigation control systems often struggle to find relevant academic work, which is typically categorized under broader fields like mechanical, aerospace, or systems engineering. Bridging this ‘cross-talk’ is essential to making academic expertise both discoverable and actionable for industry.”

To tackle this challenge, OIEx partnered with Digital Science to test two complementary generative AI approaches. At the 2025 Expert Finder Systems International Forum, Cain and Jackson Anderson (Digital Science) presented Lost in Translation? Using Generative AI to Make Academic Expertise Easier to Discover shared preliminary outcomes early insights from their pilot efforts.
Leveraging OIEx’s rich curated dataset, the team began ploring how generative AI could be used to:
- Enhance search by interpreting and translating industry partner queries, enabling intuitive discovery of academic expertise despite differing vocabularies.
- Support researchers through the use of an AI-powered wizard to generate industry-friendly bios and keywords. Better aligning academic expertise with terms familiar to practitioners could improve matchmaking.
Cain and Anderson offered perspectives on how institutions can adopt AI responsibly in research information systems—positioning these tools to support, rather than disrupt, the scholarly communication ecosystem.