Keynote Speakers
Dr. David Salac
Bio:
David Salac is an Associate Professor in the Department of Mechanical and Aerospace Engineering in the University at Buffalo. He obtained his Ph.D. in the Department of Mechanical Engineering at the University of Michigan in 2007 under the guidance of Dr. Wei Lu. From 2007 to 2010, he was a NSF Research and Teaching Grant Fellow in Engineering Sciences and Applied Mathematics at Northwestern University, working with Dr. Michael Miksis. His research interests include the modeling of soft matter systems in the presence of fluid flow and externally applied fields, multiphase fluid flow, the development of numerical methods for systems exposed to complex physics, directed self-assembly, and high-performance computing.
Title: Modeling of Moving Interfaces: From Vesicles to Rocket Engines
Abstract:
Multiphase fluid systems, ranging from boiling water to magma plumes, can be studied using similar numerical approaches. These systems often involve multiple physical phenomena, such as the interaction of electric fields and soft matter in fluids. In this talk, we will discuss our development of numerical tools, including a semi-implicit gradient-augmented level set method and a collocated grid method for incompressible Navier-Stokes equations, for tackling these complex systems. We will present sample applications of these tools, including the modeling of liposome vesicles for biotechnologies like drug delivery and the simulation of hybrid rocket engines. We will also discuss advancements like stencil composition that enable these simulations
Dr. Merouane Debbah
Bio:
Merouane Debbah is a researcher, educator and technology entrepreneur. He is a full professor at CentraleSup ́elec and Adjunct Professor at Mohamed bin Zayed University of Artificial Intelligence. Over his career, he has founded several public and industrial research centers, start-ups and is now Chief Researcher at the Technology Innovation Institute in Abu Dhabi. He is a frequent keynote speaker at international events in the field of telecommunication and AI. His research has been lying at the interface of fundamental mathematics, algorithms, statistics, information and communication sciences with a special focus on random matrix theory and learning algorithms for communication sciences. In the wireless Communication field, he has been at the heart of the development of small cells (4G), Massive MIMO (5G) and Large Intelligent Surfaces (6G) technologies, for which he received multiple distinctions.
Title: Mean-Field Games for Wireless Network Design
Abstract:
Mean field game theory is a mathematical framework that is used to analyze the behavior of a large population of agents who are interacting. In the context of wireless network design, mean field games can be used to model the behavior of users in a wireless network and to design the network in such a way as to optimize certain performance metrics, such as throughput or energy efficiency. This talk will review the basis of mean field game theory and present a mean field game-based approach to wireless network design. It will also discuss how this approach can be used to address various challenges in the design of wireless networks.
