Prof. Francesca Gardini, Università di Pavia
Tuesday, April 30, 2024, 16:00
- 17:00
Building 1, Level 3, Room 3119
We will discuss the solution of eigenvalue problems associated with partial differential equations (PDE)s that can be written in the generalised form Ax = λMx, where the matrices A and/or M may depend on a scalar parameter. Parameter dependent matrices occur frequently when stabilised formulations are used for the numerical approximation of PDEs. With the help of classical numerical examples we will show that the presence of one (or both) parameters can produce unexpected results.
Prof. Edgard Pimentel, Department of Mathematics of the University of Coimbra
Tuesday, March 26, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5220
Hessian-dependent functionals play a pivotal role in a wide latitude of problems in mathematics. Arising in the context of differential geometry and probability theory, this class of problems find applications in the mechanics of deformable media (mostly in elasticity theory) and the modelling of slow viscous fluids. We study such functionals from three distinct perspectives.
Prof. Silvia Bertoluzza
Tuesday, March 05, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5209
We present a theoretical analysis of the Weak Adversarial Networks (WAN) method, recently proposed in [1, 2], as a method for approximating the solution of partial differential equations in high dimensions and tested in the framework of inverse problems. In a very general abstract framework.
Prof. Christof Schmidhuber, ZHAW School of Engineering
Tuesday, February 27, 2024, 16:00
- 17:00
Building 9, Level 2, Room 2322
Analogies between financial markets and critical phenomena have long been observed empirically. So far, no convincing theory has emerged that can explain these empirical observations. Here, we take a step towards such a theory by modeling financial markets as a lattice gas.
Prof. Dr. Victorita Dolean, Mathematics and Computer Science, Scientific Computing, TU Eindhoven
Tuesday, February 06, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5220
Wave propagation and scattering problems are of huge importance in many applications in science and engineering - e.g., in seismic and medical imaging and more generally in acoustics and electromagnetics.
Prof. Zhiming Chen, Academy of mathematics and Systems Science, Chinese Academy of Sciences
Wednesday, January 24, 2024, 14:30
- 16:00
Building 4, Level 5, Room 5220
In this short course, we will introduce some elements in deriving the hp a posteriori error estimate for a high-order unfitted finite element method for elliptic interface problems. The key ingredient is an hp domain inverse estimate, which allows us to prove a sharp lower bound of the hp a posteriori error estimator.
Sunday, November 19, 2023, 16:00
- 18:00
Building 9, Level 2, Hall 2322
Contact Person
Quantum theory and relativity have shown the solid path for solid-state computation in the early 20th century. Since then, many theoretical breakthroughs accompanied by experimental discoveries have ultimately led us to this modern-day electronic society.
Monday, September 26, 2022, 13:00
- 14:00
Building 2, Level 5, Room 5209
Contact Person
In this thesis, we focus on the design and development of 4D printed sensors. Carbon nanotubes (CNTs) are used as the active sensing medium as they have proven to be ideal for application in sensors due to their high electric conductivity, stability, and mechanical flexibility. The effect of a heat-shrinkable substrate on the electronic and structural properties of CNTs is analyzed in depth, followed by the application in temperature, humidity, and pressure sensors. The results show that the 4D effect results in a more porous yet more conductive film due to an increase in the charge carrier concentration, enabling an improved sensitivity of the devices and allowing us to tune the selectivity based on the shrinking percentage. The developed device was fabricated using a rapid, cost-effective technique that is independent of advanced fabrication facilities to expand its applications to low-resource settings and environments.