Gábor Závodszky

I am a Computational Scientist and my research focuses on high-performance multi-scale digital twins for biomedical applications, combining expertise across three synergistic domains:

 (I) High-Performance Computing — I develop scalable computational frameworks like HemoCell, an open-source cellular blood flow simulator that achieves exceptional parallel efficiency (>80% on 300,000+ CPU cores) and enables investigations at cellular resolution that exceed current experimental capabilities.

 (II) Fundamental Biomedicine — My work advances understanding of blood rheology, platelet aggregation dynamics, and mechanosensitive processes in thrombosis through validated computational models that reproduce emergent transport characteristics of complex cellular systems.

 (III) Clinical Applications — I translate fundamental insights into actionable clinical tools, including virtual medical device deployment simulations for endovascular aneurysm treatment and patient-specific models for stroke intervention planning.

This interdisciplinary approach unlocks insights inaccessible through single-domain methods. High-performance computing enables investigations at extreme detail and accuracy, complementing experimental capabilities and accessing phenomena beyond current measurement technologies. Multi-scale computational methods bridge fundamental research and clinical practice, delivering solutions that are both achievable (optimized for performance and energy efficiency) and actionable (rigorously verified, validated, and uncertainty-quantified).

Recent projects

   ThromboRisk - (EU MSCA, Co-PI, 2025)    Vacular Immunology (Co-PI, 2025)    MMD Impulse grant (PI, 2024)    GEMINI - (EU Horizon, Co-PI, WP leader, 2024)    CompBioMed - (EU Horizon, Co-PI, WP leader, 2020)