The AI Virtual Organization (AIVO) is helping reshape how large-scale artificial intelligence research teams collaborate, coordinate, and deliver impact across disciplines.

A new paper titled Project Managers Facilitate Interdisciplinary Collaboration in AI Research brings together project managers from 25 U.S. National AI Research Institutes to examine how team science can be more effectively organized to address complex societal challenges. The study offers practical recommendations for funding agencies, universities, and research organizations on improving coordination and accelerating research outcomes.

Read the paper: Project Managers Facilitate Interdisciplinary Collaboration in AI Research

Strengthening team science in AI research

As artificial intelligence research becomes increasingly interdisciplinary, managing large research teams has grown more complex. The study identifies ongoing challenges such as communication barriers, fragmented workflows, and operational inefficiencies that can limit collaboration across institutions and disciplines.

Drawing on insights from project managers across 25 AI Institutes, the authors highlight how PMs strengthen collective intelligence, improve group dynamics, enhance operational efficiency, and support cross-disciplinary collaboration. The findings position project managers as key contributors to the success of large-scale scientific teams rather than purely administrative support roles.

Broad national collaboration across universities

The author team represents a wide network of institutions across the United States, reflecting the distributed nature of AI research coordination efforts:

Kevin Dalmeijer (Georgia Institute of Technology), Tim Robinson (University of California, Santa Barbara), Darren Cambridge (University of Maryland), Norman Gottron (Carnegie Mellon University), Marisa LaFleur (Massachusetts Institute of Technology), Candace Hulbert (Cornell University), Lauren D. Lederer (University of Washington), Spyridon Mylonas (Columbia University), Melissa Wilson Reyes (University of Oklahoma), Rajashi Runton (Duke University), Neelima Savardekar (The Ohio State University), Elise Ahn (Northwestern University), Jessica M. P. Bell (Iowa State University), Angela Berti (University of California, San Diego), Stephen F. Brown (University of California, Davis), Kher Xing Chan (University of Illinois Urbana-Champaign), Siva Jayaraman (Georgia Institute of Technology), Jordan Jobe (Washington State University), Jia Liu (The Ohio State University), Pratik Mhatre (University of Texas at Austin), Chaohua Ou (affiliation not provided), Melanie Rodriguez (University of Illinois Urbana-Champaign), Noah L. Schroeder (University of Florida), Srirangaraj Setlur (University at Buffalo), J. P. Whorley (University of Texas at Austin), Hannah B. Love (University of New Mexico), and Ellen R. Fisher (University of New Mexico).

Implications for research ecosystems

While grounded in AI research, the findings extend to other large-scale scientific collaborations. The paper emphasizes that structured project management can significantly improve coordination and increase the impact of interdisciplinary research initiatives.

AIVO’s role in advancing collaborative AI research

This work was coordinated through the AI Virtual Organization, which connects project managers and research operations leaders across AI Institutes to improve collaboration, share best practices, and strengthen team science infrastructure.

Through initiatives like this, AI4OPT continues to contribute to strengthening the operational backbone of large-scale AI research collaborations and advancing how interdisciplinary teams work together to solve complex problems.