Resources

We believe academia should be centered on sharing and supporting mutual growth. So we openly share the research vision of the group, short notes for supporting the development of early career researchers and academics, technical presentations, and whenever it is possible we share our research outcomes on open access platforms (even before peer review).

Igea F., Cicirello A., An interacting Wasserstein gradient flow strategy to robust Bayesian inference for application to decision-making in engineering, Data Centric Engineering, 2025.
Open access: https://doi.org/10.1017/dce.2025.8
Kamariotis A, Vlachas K., Dertimanis V., Koune I., Cicirello A., Chatzi E., On the consistent classification and treatment of uncertainties in Structural Health Monitoring applications, ASME J. Risk Uncertainty Part B, 2024.
Van Belle L, Deckers E., Cicirello A., Investigating and exploiting the impact of variability in resonator parameters on the vibration attenuation in locally resonant metamaterials, Royal Society Interface, 2024.
Lathourakis C., Cicirello, A., Physics Enhanced Sparse Identification of Dynamical Systems with Discontinuous Nonlinearities. Nonlinear Dynamics, 2024.
https://doi.org/10.1007/s11071-024-09652-2
Codes and experimental dataset available: https://github.com/xristosl0610/PhI-SINDy
Editor's Choice Articles of the July issue (Vol 112 - Issue 13) - paper available open access!
C Dang, A Cicirello, MA Valdebenito, MGR Faes, P Wei, M Beer, Structural reliability analysis with extremely small failure probabilities: A Quasi-Bayesian active learning method, Probabilistic Engineering Mechanics, 2024.
https://doi.org/10.1016/j.probengmech.2024.103613