DeepConnect: A Visual Analytics System for Bridging Interdisciplinary Research Collaborations
Authors
Yingchaojie Feng (National University of Singapore), Zekai Shao (Fudan University), Yiqun Sun (Magellan Technology Research Institute (MTRI)), Yixuan Tang (National University of Singapore ), Anthony K. H. Tung (National University of Singapore)
Presentation
- Session
- The more the merrier
- Time
- Tuesday, Nov 10, 10:12 – 10:24 (US/Eastern) · session 10:00 – 11:30
- Location
- Hall America north
Links
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Keywords
Visual analytics, interdisciplinary collaboration, collaborator discovery, semantic alignment
Abstract
Interdisciplinary research collaboration is crucial for scientific innovation, but it remains difficult to initiate in practice. Existing collaborator discovery approaches are often constrained by disciplinary boundaries and static researcher profiles that do not reflect the specific context of a new collaboration goal. As a result, researchers struggle to translate open-ended collaboration goals into domain-specific tasks, evaluate candidate researchers' fit and complementarity, and establish common ground before initial contact. To address these challenges, we present DeepConnect, an LLM-augmented visual analytics system for interdisciplinary collaborator discovery. DeepConnect translates collaboration ideas into domain-specific tasks, retrieves relevant papers to ground cross-domain exploration, and provides coordinated visualizations for exploring and comparing candidate researchers. It further reveals terminology gaps and overlaps across domains and supports publication-grounded conversation rehearsal to help users prepare for outreach. We evaluate DeepConnect through two case studies, a user study, and a component-level evaluation, showing its value for complementary team formation, idea refinement, and pre-contact preparation. The DeepConnect website is available at https://deepconnect.sg.
For Practitioners
Researchers seeking interdisciplinary collaborators, research managers, and developers of scholarly search tools may be interested in this work. They can apply its workflow to translate broad collaboration goals into domain-specific tasks, compare candidates using publication evidence, identify terminology gaps, and prepare more focused initial outreach.