Confirmed Semi-Plenary Speakers

Yuri Bazilevs
University of California, San Diego, USA
A Flexible Fluid-Structure Interaction Framework with Applications

Lourenco Beirao da Veiga
University of Milano Bicocca, Italy
Virtual Elements for the Stokes and Navier-Stokes equation

Antonio De Simone
SISSA, Italy
Biological and bio-inspired locomotion at small scales

Miguel A. Fernandez
Inria - CRI de Paris, France
Coupling schemes for the 3D FSI Benchmark Challenge:
comparative study and validation

Antonio Huerta
Universitat Politecnica de Catalunya, Spain
Computational vademecums for Stokes flow: transversally isotropic fluids and parameterized solutions

Thomas J.R. Hughes
The University of Texas at Austin, USA
Wherefore art thou CFD?

Chao-An Lin
National Tsing Hua University, Taiwan
Lattice Boltzmann simulations on multi-GPU cluster

Donatella Marini
University of Pavia, Italy
Virtual Elements for electromagnetic problems

Neelesh A. Patankar
Northwestern University, USA
A unifying constraint-based formulation for freely moving immersed bodies in fluids

Mats G Larson
Umea University, Sweden
CutFEM: Discretizing Geometry and Partial Differential Equations

Alessandro Reali
University of Pavia, Italy
Advanced isogeometric methods for flow and fluid-structure interaction problems

Giancarlo Sangalli
University of Pavia, Italy
Computationally efficient Isogeometric Analysis

Kenji Takizawa
Waseda University, Japan
Space-Time Slip Interface (ST-SI) Method and Its ST Friends

Tayfun Tezduyar
Rice University, Houston, USA
Space-Time Computation in FSI Analysis: It's Worth It

Alessandro Veneziani
Emory University, Atlanta (GA), USA
Computational hemodynamics for Computer Aided Clinical Trials: looking at the theory, struggling with the practice

Martin Grepl
RWTH Aachen University, Germany
Certified Reduced Basis Methods for Optimal Control and Data Assimilation

Wolfgang Wall
Technische Universitat Munchen, Germany
Enriched Computational Methods for Turbulent Flows and Fluid-Structure Interaction

Karen Willcox
Massachusetts Institute of Technology, USA
Data to decisions via multifidelity modeling and adaptive reduced models