We invite submissions for the workshop “AI for Scaling Digital Public Health: From Centres of Academic Excellence to Scaled Adoption”.
We invite submissions of extended abstracts for the workshop “AI for Scaling Digital Public Health: From Centres of Academic Excellence to Scaled Adoption”, to be held at DPH, as a 90-minute session.
Many digital health pilots start every year, yet very few scale. AI innovation is moving fast, but adoption remains slow, fragmented and unequally distributed. Innovations often fail not because they miss a real need but because the surrounding health system is not ready for them. Scaling is a system-level problem.
This workshop will explore mechanisms to building pathways that allow digital health and AI innovation to scale, leveraging from the opportunities that Centres of Academic Excellence provide to test and validate solutions and move beyond concepts faster into scalable, investable solutions.
Click here for full information on the workshop.
!! Deadlines !!
| Workshop Call for Papers (CFP) – Submission deadline | 23 December 2026 |
| Workshop Call for Papers (CFP) – Notification deadline | 28 January 2027 |
| Camera-ready deadline | 7 April 2027 |
Themes of interest
Contributions are welcomed on, but not limited to, the following themes:
- Evidence pathways for innovative digital public health interventions
- Examples of regulation by design (e.g. regulatory sandboxes, co-design processes including regulators)
- Innovation pathways enabled by AI or with AI embedded in the process, including feedback systems from testing to adoption
- Cross-sectoral innovation including partnerships across academia, government, industry, funders, and local communities.
Submission guidelines
Authors are invited to submit extended abstracts. Four abstracts will be accepted, and authors will be invited to deliver a presentation in-person at the workshop. Abstracts will be included in the DPH 2027 Abstract Book, published in Frontiers in Digital Public Health.
For submitting an Extended Abstract, please follow the instructions:
- Please format your submission using Times New Roman, 12 pt font size, with justified alignment. The submission must not exceed 1000 words, excluding the reference list. References are compulsory and should be included in the submission. A maximum of two figures or tables may be included.
- Extended Abstracts could follow the standard structure: Introduction, Background, Methods / Datasets, Results, and Conclusion. Alternatively, computer science and engineering abstracts can follow alternative structure such as Introduction, Background, Framework / Architecture, Implementation, Results (if available), Novelty and Challenges and Conclusion.
- Submissions must be anonymised: the names and affiliations removed, and any references to previous works either substituted with “anonymised” or rephrased.
- All submissions must be submitted in PDF format using the Easychair submission system. Click on the submission button below and choose the “DPH2027 Workshop – AI for Scaling Digital Public Health” track.
- Paste your first section (Aims/Abstract/Overview) to the Abstract field in the Easychair system for ease of processing and review allocation.
NOTE that:
- Abstract submissions will be reviewed by two-three reviewers from the PC and SPC committees and assessed in terms of their quality, relevance to the conference, originality, significance, correctness, and clarity.
- Accepted Extended Abstracts will have to incorporate reviewers’ comments and re-submit their abstract by the Camera-ready deadline. Instructions will be provided.
- An accepted abstract may be selected for either oral or poster presentation depending on review score and topic specificity.
Contact
Questions about this workshop can be sent to
- Dr Clara Aranda, UCL Global Business School for Health: clara.aranda@ucl.ac.uk
- Dr Dimitrios Kalogeropoulos, Global Health Digital Innovation Foundation: dimitris@ghdif.org
SUBMISSION
Submission is via EasyChair.