Hi, I am Gian Marco Melito,
Assistant Professor at the Institute of Mechanics at Graz University of Technology.
My research focuses on uncertainty quantification and sensitivity analysis of mathematical models, with a particular interest in the mechanics and modeling of aortic dissection and other cardiovascular conditions. I'm also passionate about exploring broader applications of these techniques in different fields.
I love teaching and working with students, helping them grow academically and professionally. I am currently teaching the exercise section of the Master's course in Multibody Dynamics (Mechanical Engineering program) and supporting the Bachelor's courses Mechanik - Statik and Mechanik - Dynamik for the Biomedical Engineering program.
19 - 24 July 2026
The second appointment with Computational Mechanics is still at the ECCOMAS conference, but this time in Munich (Germany).
This 1st MS explores recent advances in global sensitivity analysis for science and engineering. It focuses on how variations in model inputs affect outputs, improving understanding, robustness, and decision-making in complex, data-driven models. Topics will include sensitivity analysis with data, identifiability and parameter estimation, and explainability in scientific machine learning, all of which foster collaboration between theorists and practitioners in modern computational modeling.
The 2nd MS addresses emerging topics in cardiovascular system modeling, from methodology development to clinical translation. It highlights physics-based and data-driven approaches for understanding and predicting cardiovascular behavior. Topics include continuum and reduced-order modeling, machine learning, sensitivity and uncertainty analysis, and patient-specific applications. The session promotes interdisciplinary collaboration between applied mathematics, biomechanics, and biomedical engineering to advance personalized computational medicine.
I hope to see you there.
--- Past events ---
Computational models are widely used in science and engineering to predict complex systems, requiring a balance between model complexity and input data accuracy. This balance is crucial in applications like digital twins, where both precision and speed are necessary for decision-critical scenarios. Global sensitivity analysis helps optimize models by identifying key parameters, reducing uncertainties, and improving robustness. Various methods have been developed to address computational costs and complexities while ensuring accurate predictions. This mini-symposium seeks contributions on methodological advancements and applications of sensitivity analysis in engineering and scientific models.
It was a true pleasure to organize and participate in UNCECOMP 2025 in Greece this June. Our minisymposium was a great success, sparking thoughtful discussions despite the limited time. I am loving the sensitivity analysis community for this.
I look forward to seeing you all again, possibly at WCCM 2026 in Munich, Germany. Let us continue pushing boundaries.
Until then — stay tuned ;)