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.

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.

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.

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.

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.

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.

Power systems constitute a pillar of the critical infrastructure, and, as a result, their cybersecurity is paramount. Traditional power system architectures are moving from their original centralized nature to a distributed paradigm. This transition has been propelled by the rapid penetration of distributed energy resources (DERs) such as rooftop solar panels, battery storage, etc. However, with the introduction of new DER devices, the threat surface of power systems is inadvertently expanding.

Opportunities and Challenges in Free Space Optics:

• Inter-Satellite Communications,

Abstract

Flash floods are one of the most common natural disasters worldwide, causing thousands of

Abstract

The rampage of incessant cyber attacks have caused the disclosure of billions of users’ p

Abstract

 Deep Neural Networks (DNNs) are increasingly being used to control physical/mechani

Abstract

Cyber-physical system design involves heterogeneous components for sensing, control, actu

Abstract

Cyber-physical systems (CPS) are engineered systems that are built from, and depend upon,

Abstract

We will discuss Integrated Circuit (IC) security and trust threats and corresponding coun

Abstract

Mobile autonomous devices use sophisticated algorithms to automatically navigate diverse

The workshop aims to bring together experts to present their latest research efforts related to Embedded and Cyber Connected Systems architectures and platforms that can scale efficiently, as well as operate securely and resiliently to provide the necessary resources demanded by current and future network applications.

Available as dedicated hardware components into several mobile and server-grade processors, and recently included in infrastructure-as-a-service commercial offerings by several cloud providers, TEEs allow applications with high privacy and confidentiality demands to be deployed and executed over untrusted environments, shielding data and code from compromised systems or powerful attackers. After an  introduction to basic concepts for TEEs, I will survey some of our most recent contributions exploiting TEEs, including as defensive tools in the context of Federated Learning, as support to build secure cache systems for edge networks, as protection mechanisms in a med-tech/e-health context,  shielding novel environments (ie, WebAssembly), and more. Finally, I will highlight some of the lessons learned and offer open perspectives, hopefully useful and inspirational to future researchers and practitioners entering this exciting area of research.