The Second Biomedical Data Science Summer School and Conference

About

The Second Biomedical Data Science Summer School & Conference (BIOMED DATA 2026)
Following the success of last year’s event, we are delighted to announce the Second Biomedical Data Science Summer School & Conference (BIOMED DATA 2026), taking place in Budapest from July 06–17, 2026.

This two-part event combines intensive training in health data science with an international scientific conference dedicated to cutting-edge research in data-intensive biological and medical sciences. The two events can be attended independently, and participants may also choose to attend both as a combined two-part program.

🎓 Summer School (July 06–14, 2026)
Participants will engage in a 7-day intensive training program in biomedical data science, covering state-of-the-art methodologies in health data analytics, artificial intelligence, and network science.

📢 Conference (July 15–17, 2026)
The Conference welcomes contributions addressing challenges in data-intensive biological and medical research, with a particular focus on the development of innovative methodologies advancing biomedical discovery, including but not limited to:
• Machine learning and AI applications in biomedical research
• Multi-omics data integration and analysis
• Medical imaging and computer vision in healthcare
• Natural language processing for clinical and biomedical texts
• Explainable AI and trustworthy machine learning in medicine
• Computational modeling of biological systems
• Wearable and sensor-based health data analytics
• Privacy-preserving techniques for biomedical data
• Digital health and personalized medicine
• Drug discovery and biomarker identification through data science
• Network science tools in biomedical research
• Causal inference in biomedical research
• Biostatistical approaches for biomedical data analysis

We are honored to welcome the following distinguished Keynote Speakers:
• David Fenyő – NYU Grossman School of Medicine
• Petra Vértes – University of Cambridge
• Jörg Menche – University of Vienna
• Andreas Dengel – RPTU Kaiserslautern & DFKI

Beyond the scientific program, the Conference offers valuable networking opportunities, including a Welcome Reception with an Exhibition Talk and the Conference Dinner.

The Conference Abstract Book will be published with an ISBN number

Course leader

Gergely Palla; Kosmas Kepesidis, Luca Szegletes; Edmond Girasek

Target group

MSc and PhD students, postdoctoral researchers, and early-career researchers

Course aim

AIMS AND GOALS OF THE SUMMER SCHOOL
How can networks help us identify critical relationships in biomedical systems? How can we uncover hidden connections between genes and predict disease pathways? How can visualizing medical data improve diagnostics and treatment outcomes? How can machine learning and deep learning models transform the analysis of complex medical data?

If you're eager to explore these questions, join us at the Biomedical Data Science Summer School! This program equips participants with the theoretical foundation and practical skills to apply network science, data visualization, and machine learning to real-world biomedical challenges.

The curriculum focuses on four key areas:

Biomedical Network Science
Learn how networks can model relationships between genes, proteins, diseases, and patient data to uncover patterns and predict interactions.

Healthcare Data Sources And Visualization
Explore healthcare data sources and practical methods for creating clear, interactive visualizations of complex datasets, improving interpretability and decision-making.

Machine Learning on Tabular Medical Data
Apply machine learning techniques to structured datasets, such as electronic health records, to predict outcomes and identify risk factors.

Deep Learning on Unstructured Medical Data
Gain hands-on experience with deep learning models to analyze unstructured data, including medical images, text, and genomic sequences.

GROUP PROJECTS
Participants will work in teams on data-driven projects, applying what they learn in the courses. Mentors will provide guidance, and teams will present their results to an expert jury at the end of the program. Dedicated time is set aside for project work and presentations, ensuring a practical and engaging learning experience

Fee info

Application fee for courses and course material; Coffee breaks and a dinner at the end of the presentations; Exciting social activities (St Stephen's Basilica visit and day trip to Szentendre) ;Certificate of attendance