Edmond Chow, Professor and Associate Chair, School of Computational Science and Engineering, Georgia Institute of Technology
Tuesday, June 06, 2023, 16:00
- 17:00
Building 2, Level 5, Room 5220
Coffee Time: 15:30 - 16:00. Kernel matrices can be found in computational physics, chemistry, statistics, and machine learning. Fast algorithms for matrix-vector multiplication for kernel matrices have been developed, and is a subject of continuing interest, including here at KAUST. One also often needs fast algorithms to solve systems of equations involving large kernel matrices. Fast direct methods can sometimes be used, for example, when the physical problem is 2-dimensional. In this talk, we address preconditioning for the iterative solution of kernel matrix systems. The spectrum of a kernel matrix significantly depends on the parameters of the kernel function used to define the kernel matrix, e.g., a length scale.
Prof. Yasser Shoukry, University of California, Irvine, USA
Monday, November 28, 2022, 10:00
- 10:45
Building 2, 5220
Contact Person

Abstract

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

Prof. Panagiotis Katsaros, Aristotle University of Thessaloniki
Sunday, November 27, 2022, 14:30
- 15:15
Building 2, 5220
Contact Person

Abstract

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

Prof. Mohammad Alfaruque, University of California, Irvine, USA.
Sunday, November 27, 2022, 13:45
- 14:30
Building 2, 5220
Contact Person

Abstract

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

Prof. Ahmed Eltawil, Prof. Charalambos Konstantinou, Prof. Khaled Nabil Salama
Sunday, November 27, 2022, 08:00
- 17:00
Building 2, Level 5, Room 5220
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.
Valerio Schiavoni, Scientific Coordinator and Lecturer, Centre of Competence for Complex Systems and Big Data, University of Neuchâtel
Thursday, November 11, 2021, 12:00
- 13:00
Building 9, Level 3, Room 3223, https://kaust.zoom.us/j/96526753797
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.