Abdullah Almansouri, PhD Student, Electrical and Computer Engineering, KAUST
Thursday, April 01, 2021, 16:00
- 17:00
https://kaust.zoom.us/j/94736907194
Contact Person
The next technological revolution, Industry 4.0, is envisioned as a digitally connected ecosystem where machines and gadgets are driven by artificial intelligence. By 2025, more than 75 billion devices are projected to serve this revolution. Many of which are to be integrated into the fabrics of everyday life in the form of smart wireless sensors. Still, two major challenges should be addressed to realize truly wireless and wearable sensors. First, the sensors should be flexible and stretchable, allowing for comfortable wearing. Second, the electronics should scavenge the energy it requires entirely from the environment, thus, eliminating the need for batteries, which are bulky, create ecological problems, etc. By addressing these two challenges, this dissertation paves the way for truly wearable sensors.
Thursday, April 01, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/94262797011?pwd=ZXBBcnltQ3JvZkdhWFZjTEptL3FmUT09
Contact Person
Wave functional materials are artificial materials that can control wave propagation as wish. In this talk, I will give a brief review on the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties. In particular, I will focus on our contributions on metamaterials and metasurfaces. I will introduce the development of effective medium, a powerful tool in modeling wave functional materials, followed by some illustrative examples demonstrating the intriguing properties, such as redirection, emission rate enhancement, wave steering and cloaking.
Jean Oh, Senior Systems Scientist, Robotics Institute, Carnegie Mellon University
Wednesday, March 31, 2021, 16:30
- 17:15
https://kaust.zoom.us/j/99217498463
Contact Person
For more information please visit the website
Maha Al-Aslani, PhD Student, Computer Science, KAUST
Wednesday, March 31, 2021, 16:00
- 17:00
https://kaust.zoom.us/j/7665815153
Contact Person
In this thesis defense, I will explore the unique characteristics of IoT traffic and examine IoT systems. The work is motivated by the new capabilities offered by modern Software Defined Networks (SDN) and blockchain technology. We evaluate IoT Quality of Service (QoS) in traditional networking. We obtain mathematical expressions to calculate end-to-end delay, and dropping. Then, we analyze IoT traffic load and propose an intelligent edge that can identify volumetric traffic and address them in real-time using an instantaneous detection method for IoT applications (IDIoT). This approach can easily detect a large surge and potential variation in traffic patterns for an IoT application, which may contribute to safer and more efficient operation of the overall system. Our results provide insight into the advantages of an intelligent edge serving as a detection mechanism.
Rui Chen, PhD Student, Electrical and Computer Engineering, KAUST
Wednesday, March 31, 2021, 16:00
- 18:00
https://kaust.zoom.us/j/97237199129
Contact Person
Time-domain methods are preferred over their frequency-domain counterparts for solving acoustic and electromagnetic scattering problems since they can produce wide-band data from a single simulation. Among the time-domain methods, time-domain surface integral equation solvers have recently found widespread use because they offer several benefits over differential equation solvers. This dissertation develops several second-kind surface integral equation solvers for analyzing transient acoustic scattering from rigid and penetrable objects and transient electromagnetic scattering from perfect electrically conducting and dielectric objects. For acoustically rigid, perfect electrically conducting, and dielectric scatterers, fully explicit marching-on-in-time schemes are developed for solving time domain Kirchhoff, magnetic field, and scalar potential integral equations, respectively.
Stefan B. Williams, Head of School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney
Wednesday, March 31, 2021, 12:00
- 12:45
https://kaust.zoom.us/j/99217498463
Contact Person
For more information please visit the website
Mathieu Laurière, Postdoc, Operations Research and Financial Engineering, Princeton University, USA
Tuesday, March 30, 2021, 14:30
- 17:30
https://kaust.zoomus/j/91484640398
Contact Person
Mean field games and mean field control problems are frameworks to study Nash equilibria or social optima in games with a continuum of agents. These problems can be used to approximate competitive or cooperative situations with a large finite number of agents, and have found a broad range of applications, from economics to crowd motion, energy production and risk management. The solutions are typically characterized by a forward-backward system of partial differential equations (PDE) or stochastic differential equations (SDE).