• Digital Dermatology and Clinical Innovation
  Development and evaluation of digital approaches to support diagnosis, monitoring, and management of skin diseases, with a strong focus on clinical relevance and real-world applicability.
• Artificial Intelligence and Data-Driven Dermatology
  Application of machine learning and artificial intelligence, including large language models, to dermatological data for image analysis, pattern recognition, and clinical decision support, with emphasis on transparency, validation, and safe clinical integration.
• Digital Imaging and Advanced Phenotyping
  Use of two- and three-dimensional imaging technologies combined with advanced data analysis to improve disease phenotyping, longitudinal monitoring, and outcome assessment in dermatology.
• Telemedicine and Hybrid Care Models
  Investigation of teledermatology and digital medical solutions as scalable strategies to improve access to dermatological care, continuity of treatment, and efficiency within healthcare systems.
• Wearables and Sensor-Based Skin Health Monitoring
  Evaluation of wearable and sensor-based technologies for monitoring skin health and relevant systemic parameters, with attention to feasibility, patient acceptance, and clinical benefit.
• Real-World Evidence and Population-Based Dermatology
  Large-scale observational and comparative effectiveness studies using federated, multi-institutional real-world clinical data to analyze disease trajectories, comorbidities, treatment patterns, and outcomes.
• Skin Health Epidemiology and Spatial Analysis
  Application of epidemiological methods, spatial analyses, and data science approaches to investigate population-level patterns, environmental influences, and outcomes of skin diseases.
• Preventive Dermatology and Public Health
  Development and evaluation of preventive strategies, early detection approaches, and population-based interventions aimed at improving long-term skin health and health equity.
• Digital Data Sources and Emerging Population Signals
  Exploration of novel digital data sources, including crowdsourcing approaches and selected internet-based signals, to complement classical epidemiological research where they provide methodological value.

Key figures

• Publications indexed in PubMed: > 250
• Cumulative impact factor: > 1,400
• Third-party funding: > € 6.5 million
• The group’s research bridges clinical dermatology, population-based epidemiology, and digital medicine within coherent, long-term research programs. Rather than pursuing isolated projects, we develop structured research lines that translate scientific insight into sustainable improvements in healthcare delivery. Our aim is to combine methodological rigor with real-world implementation, creating durable academic and clinical impact.