The Office of Business Engagement (OBE) and Data Science Institute (DSI) have launched a new tool that helps university faculty and staff discover relevant research, shared interests and potential collaborators across campus.
RABBIT (Research and Business-Bridging Intelligence Tool) is an AI-powered faculty discovery tool that is available to all UW–Madison faculty and staff, and WARF employees, with a NetID. It was designed and developed by OBE and DSI to help industry engagement offices on campus connect faculty with applied research opportunities.
“So much of what I do is trying to find the expertise we have around campus to work on, apply to, and create projects and research collaborations,” says Alyson Fleming, Director of Public-Private Partnerships at the Nelson Institute for Environmental Studies. Fleming, who served as a beta tester for RABBIT, uses the tool both for her work with industry and for campus collaborations facilitated through the Sustainability Research Hub.
RABBIT helps faculty and staff who seek researchers on campus with specific expertise. A search for a UW–Madison faculty member in RABBIT results in a high-level summary of their work, including a map of their campus collaborations. The search also yields publicly available information about their articles, grants, patents, sponsorships and agreements. RABBIT provides information about sponsored research and papers co-authored with industry—valuable in finding matches between companies and researchers for sponsored research or co-applications for federal grants.
Increasingly, funders such as the National Science Foundation are prioritizing research that cuts across academic disciplines. RABBIT is a new way UW–Madison researchers can find collaborators in other colleges and schools and form multidisciplinary teams. This can be particularly useful for new employees navigating the breadth and depth of expertise on campus.
“We thought a lot about the RISE initiative and how RISE hires will be pursuing multidisciplinary research,” says Sara Braas, Associate Director of OBE. “This tool will be perfect for new faculty on campus, whose networks are still developing, to understand who’s working on the things they’re interested in and build those research partnerships.”
OBE and DSI developed RABBIT to help UW–Madison build better industry partnerships and connect more companies with faculty through sponsored research agreements. Braas envisions a tool that quickly identifies all UW–Madison faculty whose expertise matches industry needs—especially faculty new to campus who might not yet be on the radar of industry engagement offices.
“Public-private partnership opportunities around shared research interests are expanding,” says Braas, “and federal grants increasingly require an industrial partner. RABBIT helps make those important connections by allowing us to find the faculty working in specific research areas.”
Braas initially looked to the marketplace for a software solution that would support campus-industry matchmaking efforts, but nothing available fit her requirements. After learning about an exploratory initiative to build a faculty search tool, led by DSI Director Kyle Cranmer, she turned to DSI for a custom solution.
“It couldn’t have gone better,” says Braas. “We were able to really customize the tool by working with the fabulous team at DSI.”
RABBIT beta tester Russ Johnson, Director of the Office of Corporate Relations in the College of Engineering, appreciates that RABBIT can do a faster, more far-reaching search for faculty matches than a typical web search. He also likes that the RABBIT interface is straightforward and doesn’t take long to learn.
RABBIT works differently from the keyword-based searches that power most search engines. DSI Research Software Engineer Abe Megahed explains how RABBIT uses an AI-powered semantic search.
“The limitation with tools like Google and other search engines is that you sometimes need to hit upon just the right keywords,” says Megahed. “It can be a challenge. The innovative thing about RABBIT that solves this problem is called a semantic search. You submit a block of text, and it looks for all the people that are in that space. The search is based on meaning, rather than keywords.”
Megahed says that RABBIT provides the best results when users enter blocks of text. This text could be a passage from a request for proposals or a description of a problem a company is trying to solve. A user could even type keywords into a generative AI tool like Copilot and then plug the resulting text into RABBIT. If RABBIT returns many matches, users can narrow search results by using filters built into the tool.
“We used to just search Google and see what comes back from people’s individual UW profiles,” says Fleming. “I feel like this does a much more rigorous scrub. That’s really reassuring and gives me a lot more confidence that, when we reach out to someone, we know they are among the best fits on campus.”
UW–Madison faculty and staff and WARF employees can access RABBIT by going to rabbit.obe.wisc.edu and logging in with their NetID. For questions about RABBIT, please contact Sara Braas in the Office of Business Engagement.
— Cris Carusi
RABBIT Credits: RABBIT was created by a team from the Office of Business Engagement and the Data Science Institute, powered by American Family Insurance:
Office of Business Engagement: Sara Braas and John Garnetti
Data Science Institute: Kyle Cranmer, Jason Lo and Abe Megahed