SFB 1313 Anneliese Niethammer Lecture with by Valentina Ciriello

February 10, 2026 /

The SFB 1313 "Pretty Porous Science Lecture" #73 will be given by Valentina Ciriello | University of Bologna (Italy) | 10 February 2026 | 4 pm CET

We are pleased to announce that Valentina Ciriello, associate professor at the University of Bologna (Italy), will give the SFB 1313 "Pretty Porous Science Lecture" #73. Her talk will be on "Extracting Insight from Complexity Through Model Reduction of Groundwater Processes".

Date: 10 February 2026
Time: 4 pm
Speaker: Associate Prof. Dr. Valentina Ciriello, University of Bologna (Italy)
Title: "Learning from complexity: model reduction in porous media research"
Venue: Multi Media Lab (MML), U1.003, Pfaffenwaldring 61, 70569 Stuttgart, Campus Vaihingen. If you are interested in participating in the lecture online, please contact samaneh.vahiddastjerdi@mechbau.uni-stuttgart.de

Abstract

Flow and transport processes in porous media pose significant computational and interpretive challenges. High-fidelity numerical models are essential to capture these processes; however, their computational cost limits the systematic exploration of uncertainty, parameter variability, and scenario analysis. Model reduction techniques are increasingly adopted to enable faster simulations, but their potential extends well beyond computational acceleration. This seminar presents a unified perspective on model reduction for porous media research, emphasizing its role as a framework for extracting dominant dynamics, identifying governing drivers, and improving physical interpretation. Reduced-order representations of dynamic processes are discussed, highlighting how modal decompositions can isolate coherent spatiotemporal patterns and reveal the mechanisms underlying complex behaviors. Surrogate modeling strategies based on neural networks combined with transfer learning, as well as polynomial chaos expansions, are introduced as tools to quantify uncertainty and characterize variability in quantities of interest through global sensitivity analysis. Together, these approaches demonstrate how model reduction can support faster simulations while simultaneously guiding data acquisition, reducing uncertainty, and enabling a more comprehensive understanding of physical processes.

About Valentina Ciriello

Dr. Ciriello is an Associate Professor in the Department of Civil, Chemical, Environmental, and Materials Engineering at the University of Bologna. Her research interests include data-driven modeling and simulation, response surface methods, global sensitivity analysis, and uncertainty quantification, with applications spanning fluid mechanics, hydrology, and biomedical engineering.

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