Dr Sandra Barteit ↗
Research Group Lead / Principal Investigator
Role / research source ↗Data architecture and AI · Heidelberg · Research partnerships in Africa and Asia
PULSE-AI
Using graph databases and AI to investigate complex relationships between climate exposure and health.
Research programme · 2023–2028
Connected methods research
Project objectives
Objectives
- Develop graph-based approaches for connecting person, household, environmental and health observations.
- Investigate AI methods for understanding complex climate-health patterns and data-quality challenges.
- Support reproducible research questions across linked data scales and institutional collaborations.
The research question
What becomes visible when climate and health data can be analysed together across scales?
Research approach
Research approach
Established in October 2023, the Carl Zeiss Foundation NEXUS research group develops methods for connected climate and health data. Graph databases preserve relationships between people, households, places and observations; AI methods are investigated for understanding risk patterns and identifying research priorities.
Host: Digital Global Health, HIGH · Support: Carl Zeiss Foundation NEXUS
People & contributions
Research roles and contributions
PULSE-AI develops graph-based data integration and analytical methods that inform how heterogeneous CHEERS observations can be connected and studied.
Partners & connections
Partner institutions
Heidelberg Institute of Global Health (HIGH) ↗
Digital Global Health, shared methods and academic research collaboration
Carl Zeiss Foundation ↗
Funding through the NEXUS programme
Monash University Malaysia / SEACO ↗
Population-platform cooperation partner
Centre de Recherche en Santé de Nouna (CRSN) ↗
Population research cooperation partner
BTU Cottbus-Senftenberg · Digital Public Health ↗
Digital public health cooperation partner
Partner roles refer to the research and institutional connections documented in the linked sources.
Current status · 12 November 2026
Research programme · 2023–2028
PULSE-AI is a 2023–2028 Carl Zeiss Foundation NEXUS programme at HIGH. A 2026 knowledge-graph paper documents data integration using Nouna observations. Related AI work is research on methods and data quality; prospective clinical usefulness and early-warning performance require separate evaluation.
Publications & evidence
Related publications
The labels distinguish project or site publications from related studies and shared methods. Protocols describe research designs, rather than proven health effects.
2026Associated data-methods studyData architecture
Design and Implementation of a Knowledge Graph for Integrating Global Health Data Using Neo4j ↗
Shows how Nouna population, weather, wearable and indoor climate datasets can be linked in a knowledge graph.
Methods, findings & limitations ↗2026Related AI-methods researchAI & data quality
Overcoming Data Loss in Wearable Disease Detection with GAN-Based Imputation ↗
Studies generative reconstruction of missing wearable heart-rate data and its potential to support disease-signal detection.
Methods, findings & limitations ↗2023Shared frameworkMethods
Widening the lens of population-based health research to climate change impacts and adaptation: the climate change and health evaluation and response system (CHEERS) ↗
Introduces the modular CHEERS framework linking population surveillance, environmental measurements and individual health data.
Methods, findings & limitations ↗Research settings
Research settings
Sources & updates
Sources and updates
- PULSE-AI programme ↗
- Knowledge graph study ↗
- Institutional programme announcement ↗
- Public contact / role: Dr Sandra Barteit ↗
Profile reviewed 12 November 2026. Suggest a profile update ↗