Research Jam is a collegial and developmental forum — grown, over five years, from an informal conversation among a small group of researchers into a regular gathering of like-minded scholars who share their work through candid and constructive discussion.
This year's edition, hosted by KIN Center for Digital Innovation, brought together 35 participants from research institutions across the world, including the Netherlands, Australia, the United Kingdom, Canada, Austria, Italy, France, and Argentina.
Two days of scholarly exchange
The fifth edition also marked the second year of the PhD Track, featuring three parallel sessions covering the organizing, safety, and implementation of healthcare technologies (chaired by Giulia Cappellaro); relational expertise and the reconfiguration of professional boundaries (chaired by Sylvaine Tuncer); and AI in practice as emerging technologies changing knowledge work (chaired by Mohammad Hosein Rezazade Mehrizi).
Across four plenary sessions, the programme ranged widely: from how digital self-tracking technologies assemble user agency and contested health discourses, to interprofessional coordination and EMR workarounds; from AI drift and governance challenges, to expertise development in gastroenterology, temporal work in quality improvement, and the role of patient online communities in reshaping professional jurisdiction. Every study was met with rich discussion and a wave of questions — exactly the spirit the Jam was built for.
Organizers and sponsors
The fifth edition was organized by Sylvaine Tuncer (King's Business School), Giulia Cappellaro (Bocconi University), and Mohammad Hosein Rezazade Mehrizi (KIN Center for Digital Innovation, VU Amsterdam) with the support of local organizers, Katja Teniaeva and Florence Goes.
The event was sponsored by SHOC — the Society for Studies in Organizational Healthcare — and the LIAISON project. LIAISON is a collaboration of organizations working toward the effective deployment of novel algorithmic technologies in healthcare, bringing together communities of medical practitioners, technology developers, governance and policy actors, and patients to shift the state of medical AI from a technology problem into a learning challenge.
