We are in the process of curating a list of this year’s publications — including links to social media, lab websites, and supplemental material. Currently, we have 96 full papers, 19 posters, one journal paper, two interactive demos, two student mentoring programs and we lead six workshops. Three papers received a best paper award and 11 papers received an honorable mention.
Your publication from 2026 is missing? Please enter the details in this Google Forms and send us an email that you added a publication: contact@germanhci.de
Advancing Co-located and Distributed Multi-user Mixed Reality
Katja Krug (Interactive Media Lab Dresden, TUD Dresden University of Technology)
Abstract | Tags: Student Mentoring Program (SMP) | Links:
@inproceedings{Krug2026AdvancingColocated,
title = {Advancing Co-located and Distributed Multi-user Mixed Reality},
author = {Katja Krug (Interactive Media Lab Dresden, TUD Dresden University of Technology)},
url = {https://imld.de/, website
https://www.linkedin.com/company/iml-dresden/, lab's linkedin
www.linkedin.com/in/katja-krug, author's social media},
doi = {10.1145/3772363.3799196},
year = {2026},
date = {2026-04-13},
urldate = {2026-04-13},
abstract = {Mixed Reality (MR) enables new forms of social interaction by blending physical and virtual spaces across co-located, distributed, and hybrid settings. In these environments, interpersonal encounters are shaped not only by technical constraints but also by interaction design, perception, and social dynamics. In my research, I investigate key questions across these dimensions and contribute to a deeper understanding of multi-user MR system development and of how people perceive, interact, and engage with one another in shared MR spaces. To this end, we conducted a structured review of design and research challenges in multi-user MR systems, explored interaction strategies that support collaborative activity while preserving social and contextual awareness, and examined how avatar self-views influence communication and attention in multi-user scenarios. My next steps include exploring how MR visualizations can support and mediate social dynamics and collaborative flow in group meeting contexts.},
keywords = {Student Mentoring Program (SMP)},
pubstate = {published},
tppubtype = {inproceedings}
}
Mixed Reality (MR) enables new forms of social interaction by blending physical and virtual spaces across co-located, distributed, and hybrid settings. In these environments, interpersonal encounters are shaped not only by technical constraints but also by interaction design, perception, and social dynamics. In my research, I investigate key questions across these dimensions and contribute to a deeper understanding of multi-user MR system development and of how people perceive, interact, and engage with one another in shared MR spaces. To this end, we conducted a structured review of design and research challenges in multi-user MR systems, explored interaction strategies that support collaborative activity while preserving social and contextual awareness, and examined how avatar self-views influence communication and attention in multi-user scenarios. My next steps include exploring how MR visualizations can support and mediate social dynamics and collaborative flow in group meeting contexts.
Investigating Implicit Adaptivity of an LLM-based Companion for low-acuity Patients in the Emergency Department
Jacobe Klein (Freie Universität Berlin)
Abstract | Tags: Student Mentoring Program (SMP) | Links:
@inproceedings{Klein2026InvestigatingImplicit,
title = {Investigating Implicit Adaptivity of an LLM-based Companion for low-acuity Patients in the Emergency Department},
author = {Jacobe Klein (Freie Universität Berlin)},
url = {https://www.mi.fu-berlin.de/en/inf/groups/hcc/index.html, website
https://www.linkedin.com/in/jacobe-klein, author's linkedin},
doi = {10.1145/3772363.3799203},
year = {2026},
date = {2026-04-13},
urldate = {2026-04-13},
abstract = {In emergency departments (ED), patients' experiences often involve needs beyond medical care, including empathetic communication while feeling seen and informed. My thesis aims to address a care gap caused by staffing constraints and high patient numbers: advancements in artificial intelligence (AI) offer an opportunity to support low-acuity patients during passive waiting times through an AI companion that prepares for consultation, provides information on ED processes, and offers empathetic support without replacing clinical staff. Based on workshops and patient interviews, preliminary requirements for this companion concept were gathered. Building on these insights, my next steps focus on investigating how the companion can implicitly adapt its role and behavior to individual patients, without the cognitive burden of explicitly customizing it. My thesis contributes to the growing body of literature on patient-facing conversational AI and explores how adaptive systems can enhance patient experiences while supporting clinical workflows in high-stress ED settings.},
keywords = {Student Mentoring Program (SMP)},
pubstate = {published},
tppubtype = {inproceedings}
}
In emergency departments (ED), patients' experiences often involve needs beyond medical care, including empathetic communication while feeling seen and informed. My thesis aims to address a care gap caused by staffing constraints and high patient numbers: advancements in artificial intelligence (AI) offer an opportunity to support low-acuity patients during passive waiting times through an AI companion that prepares for consultation, provides information on ED processes, and offers empathetic support without replacing clinical staff. Based on workshops and patient interviews, preliminary requirements for this companion concept were gathered. Building on these insights, my next steps focus on investigating how the companion can implicitly adapt its role and behavior to individual patients, without the cognitive burden of explicitly customizing it. My thesis contributes to the growing body of literature on patient-facing conversational AI and explores how adaptive systems can enhance patient experiences while supporting clinical workflows in high-stress ED settings.