In this UbiComp 2026 workshop, we are hoping to bring together researchers, clinicians, practitioners, and industry professionals to critically examine how artificial intelligence can responsibly augment ubiquitous computing systems for mental health, and to discuss the opportunities and risks this introduces for research, clinical practice, and real-world deployment.
Find Out MoreUbiquitous computing technologies (UbiComp) have long served as crucial tools for collecting behavioral, physiological, social, and environmental data to enable early symptom detection, deliver preventative interventions, and support ongoing symptom management. With over a decade of success in demonstrating the feasibility of using UbiComp technologies to support well-being and mental health in both general and clinical populations, the field is now witnessing a rapid integration of artificial intelligence (AI) and generative AI in particular into the sensing, inference, and intervention pipelines it has spent years developing. This convergence introduces new opportunities, such as personalized and context-sensitive interventions and scalable clinical decision support. However, it also introduces risks that the field has not yet systematically addressed, including model brittleness across populations and deployment contexts, hallucination in AI-generated clinical interpretations, and insufficient transparency for general and clinical accountability.
This workshop aims to bring together researchers, clinicians, practitioners, and industry professionals to collaboratively examine this convergence, identify shared research priorities, and develop community standards for responsible innovation at the intersection of UbiComp and AI in mental health. We are calling for papers that address these challenges from technical, clinical, or ethical perspectives. Building on ten years of success, we continue to support the UbiComp community in navigating the opportunities and risks that AI integration introduces into research, clinical practice, and real-world deployment.
We are introducing a special call for workshop papers that not only explore innovative AI-enabled approaches but also critically reflect on their implications, risks, and responsible deployment in real-world contexts. We encourage submissions that present early-stage findings or exploratory ideas that may not yet be fully developed for archival publication but are valuable to the community.
Relevant topics may include, but are not limited to:
Clinical validation, real-world deployment, and scalable implementation of AI-integrated UbiComp interventions.
Datasets, community benchmarks, and evaluation standards for UbiComp mental health systems across diverse populations and clinical contexts.
Foundation models and AI-integrated UbiComp pipelines for mental health and well-being support (e.g., mental health inference, emotional support, clinical decision-making).
Longitudinal personalization and context-aware adaptation in UbiComp mental health and well-being systems.
Long-term integration and sustainable adoption of UbiComp mental health technologies in healthcare systems.
Multimodal and longitudinal sensing data collection, integration, and quality for AI-driven mental health contexts.
Novel sensing modalities and hardware innovations for mental health monitoring beyond conventional smartphone and wearable platforms.
Responsible and trustworthy UbiComp mental health and well-being systems (e.g., transparency, interpretability, fairness, and accountability).
Submission deadline: 25th June, 2026
Decisions to authors: 5th July, 2026
Camera-ready deadline: 15th July, 2026
Workshop: 11th or 12th October, 2026 (TBD)
All items due 11:59 PM AoE
We are soliciting six types of contributions (see below). Papers should be submitted using the UbiComp/ISWC 2026 proceedings format. Papers should be in PDF format and not anonymized.
To submit, please use the below details: https://new.precisionconference.com/
Society: SIGCHI
Conference: UbiComp/ISWC 2026,
Track: UbiComp/ISWC 2026 Mental Health
We are soliciting six types of contributions for the workshop as follow:
Scientific papers describing novel technologies, approaches, datasets, or empirical findings at the intersection of ubiquitous sensing and AI for mental health. We encourage these submissions to focus on learnings that are beneficial for the community and not finished contributions.
Challenge papers, in which authors articulate a specific challenge to be pitched and discussed at the workshop. These papers often lead to a lively discussion during the workshop and to new directions for future work.
Experience reports detailing the deployment of AI-integrated UbiComp systems in real-world mental health contexts, including systematic documentation of implementation barriers, user engagement outcomes, clinical workflow integration, and lessons learned.
Critical reflections on methodological assumptions, evaluation norms, or ethical frameworks at the intersection of ubiquitous computing, AI, and mental healthcare. We expect critical reflection papers to contribute towards better research practices in the community.
Dataset papers, in which authors document new datasets from clinical or underrepresented populations, including data collection methodology, participant characteristics, known limitations, and guidance for responsible community reuse.
Demonstrations of working systems accompanied by a short paper describing the sensing architecture, evaluation approach, and preliminary findings.
Submissions may be up to 6 pages in length, including figures and references. Shorter papers (e.g., 3-page submissions) are also welcome.
All submissions should be formatted using the 2-column ACM proceedings template.
This workshop uses a single-blind review process; all submissions must include the names and affiliations of all authors.
All submitted papers will be reviewed and judged on originality, technical correctness, relevance, and quality of presentation. We explicitly invite submissions of papers that describe preliminary results or work-in-progress, including early translational experiences.
The accepted papers will appear in the UbiComp supplemental proceedings and in the ACM Digital Library (DL). Authors of accepted papers will be invited to present their work in person and receive feedback from attendees. We plan to have a fully in-person workshop in Shanghai, China.
Please also see this general guideline if you plan to submit your accepted paper archived in ACM DL to other peer-reviewed venues, like IMWUT. — IMWUT, by default, UbiComp workshop papers are not considered for publication in IMWUT. The authors are also allowed to "re-use and re-submit the content to other peer-reviewed venues”. The new manuscript would require at least 25% of new material (conceptually, not just text) per ACM guidelines, and, in this case, it would be prudent to include the previous submission together with the new one.
You can also “choose not to" archive your accepted paper in ACM DL. In this case, please notify the organizers once your paper has been accepted.
| Time (Local to Shanghai, China) | Event |
|---|---|
| 9:00 AM - 9:30 AM | Opening remarks |
| 9:30 AM - 10:30 AM | Keynote speaker 1: TBD |
| 10:30 AM – 11:00 AM | Speed networking and coffee break |
| 11:00 AM – 12:30 PM | Workshop paper feedback sessions
To be announced after notification (July 2026). |
| 12:30 PM - 2:00 PM | Networking lunch with workshop attendees |
| 2:00 PM – 4:00 PM | Group discussion and brainstorming with attendees:
Potential topics:
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| 4:00 PM – 5:00 PM | Keynote speaker 2: TBD |
| 5:00 PM - 5:15 PM | Coffee break (with the main conference itself) |
| 5:15 PM – 5:30 PM | Closing remarks and best paper award |
| 6:00 PM – 8:00 PM | Networking dinner with workshop attendees |
We will invite two keynote speakers representing complementary perspectives: one from clinical or translational research with experience deploying UbiComp systems in real-world mental health settings, and one from the AI or sensing research community addressing the opportunities and risks of integrating foundation models and generative AI into mental health pipelines. We aim to include a speaker from the Asia-Pacific region to reflect the geographic diversity of the workshop community.
Abstract:
To be announced.
Abstract:
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To be announced.