Events

Oct 16 - Oct 22, 2022

Inference for Longitudinal Data After Adaptive Sampling

Prof. Susan Murphy, Statistics and Computer Science and Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University

Oct 20, 15:00 - 16:00

B9 L2 H2

Reinforcement Learning

In this work, we proved statistical inference for the common Z-estimator based on adaptively sampled data. Adaptive sampling methods, such as reinforcement learning (RL) and bandit algorithms, are increasingly used for the real-time personalization of interventions in digital applications like mobile health and education. As a result, there is a need to be able to use the resulting adaptively collected user data to address a variety of inferential questions, including questions about time-varying causal effects.
We used Reinforcement Learning; but did it work?

Prof. Susan Murphy, Statistics and Computer Science and Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University

Oct 19, 16:00 - 17:00

B9 L2 H2

Reinforcement Learning Digital Behavioral Health

Reinforcement Learning provides an attractive suite of online learning methods for personalizing interventions in Digital Behavioral Health. However, after a reinforcement learning algorithm has been run in a clinical study, how do we assess whether personalization occurred? We might find users for whom it appears that the algorithm has indeed learned in which contexts the user is more responsive to a particular intervention. But could this have happened completely by chance? We discuss some first approaches to addressing these questions.
Gradient Estimates for weak solutions of Elliptic PDE's - Colloquium

Giuseppe Di Fazio, Professor, University of Catania

Oct 18, 15:30 - 17:00

B1 L3 R3119

Elliptic PDE

In the Seminar, we exploit what is the heart of the technique to show gradient estimates allowing the function ? to belong to very general function spaces. Our technique is very flexible and allows us to show the existence, uniqueness, and well-posedness of the Dirichlet problem in several classes.
Distributed multi-GPU Algorithms for Hierarchical Matrices

George Turkiyyah, Research Professor, Applied Mathematics and Computational Sciences

Oct 18, 12:00 - 13:00

B9 L2 R2322

GPU Algorithms hierarchical matrices

In this talk, we show that, besides their optimal O(N) algorithmic complexity, hierarchical matrix operations also benefit from parallel scalability on distributed machines with extremely large core counts. In particular, we describe high-performance, distributed-memory, GPU-accelerated algorithms for matrix-vector multiplication and other operations on hierarchical matrices in the H^2 format.
Recent advances in mixed finite element approximation for poroelasticity

Arbaz Khan, Assistant Professor, Department of Mathematics, Indian Institute of Technology (IIT)

Oct 18, 11:00 - 12:00

B1 L3 R3119

parallel computing Numerical Solution of Partial Differential Equations stochastic differential equations

This talk discusses the non-conforming approximation of Biot's consolidation model. In the first part of the talk, we discuss posteriori error estimators for locking-free mixed finite element approximation of Biot’s consolidation model. In the second part of the talk, we discuss a novel locking-free stochastic Galerkin mixed finite element method for the Biot consolidation model with uncertain Young’s modulus and hydraulic conductivity field.

Oct 9 - Oct 15, 2022

Oct 2 - Oct 8, 2022

Sep 25 - Oct 1, 2022

Sep 18 - Sep 24, 2022

Sep 11 - Sep 17, 2022

Sep 4 - Sep 10, 2022

Aug 28 - Sep 10, 2022

Compound Semiconductor Weekend

Integrated Photonics Laboratory; Smart, Advanced Memory devices and Applications Laboratory; Photonics Laboratory; Advanced Semiconductor Laboratory

Sep 3, 09:00 - Sep 5, 17:00

B3 L5 R5209

The Compound Semiconductor Weekend will focus on some of the most important research areas on the beautiful KAUST campus by the Red Sea. It features 18 invited and contributed oral talks and a poster competition. Semiconductor technology is a major foundation of the third and fourth Industrial Revolutions as well as the modern society. While silicon remains as the widest-employed semiconductor, compound semiconductors have emerged from lab research to becoming the second most widely used within a short period of time. This is because compound semiconductors could possess multiple superior key properties simultaneously. They include high speed, high power, and efficient light emission and absorption, as well as that they can be produced in large scale at low cost and are highly robust. As a result, they have become cornerstones of many crucial technologies including lighting, display, communication, space exploration, and electric vehicles. While semiconductor researchers are plowing deeper for those technologies, compound semiconductors attract increasing attention for future computing, memory, and quantum information science as the pursuit of Moore’s Law has slowed down dramatically when the size of silicon transistors is approaching the physical limit of a few atoms.

Aug 28 - Sep 3, 2022

Jul 24 - Jul 30, 2022

Communications, Computing, and Security for the Internet of Things Era and Beyond

Hesham Elsawy, Assistant Professor, Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM)

Jul 26, 16:00 - 17:00

B1 L3 R3119

communications computing

This talk will first discuss the communications, computation, and security challenges for the IoT era and motivate a systematic methodology to address them. The talk will then overview some relevant problems and their potential solutions. Future research direction will also be highlighted.

Jul 17 - Jul 23, 2022

Jul 3 - Jul 9, 2022

Mean-Field Games on Networks and Wardrop Equilibria - PhD Dissertation Defense

Fatimah H. Al Saleh, PhD Student, Applied Mathematics and Computational Sciences, KAUST, Saudi Arabia

Jul 6, 10:00 - 12:00

KAUST

This thesis consists of three main parts. In the first part, we discuss first-order stationary mean-field games (MFGs) on networks. In the second part, we discuss the Wardrop equilibrium model on networks with flow-dependent costs and its connection with stationary MFGs. First, we build the Wardrop model on networks. Second, we show how to convert the MFG model into a Wardrop model. Next, we recover the MFG solution from the Wardrop solution. Finally, we study the calibration of MFGs with Wardrop travel cost problems. In the third part, we explain the algorithm for solving the algebraic system associated with the MFG numerically, then, we present some examples and numerical results.
Integrated Photonic Devices for Sensing and Telecom Applications

Prof. Hugo E. Hernandez Figueroa, University of Campinas (UNICAMP)

Jul 6, 10:00 - 11:30

B3 L5 R5209

Integrated Photonics technology

This talk will be focused on Integrated Photonics technology, which demands strong and robust confinement of light in order to attain the maximum possible integration of photonics devices on a single chip. Keeping this in mind, three applications based on LEMAC’s recent developments will be presented in this talk.
Metaverse Virtual Service Management: Game Theoretic Approaches

Prof. Dusit Niyato, Computer Science and Engineering, Nanyang Technological University, Singapore

Jul 5, 10:45 - 12:05

KAUST

Metaverse Virtual Service Management

Metaverse is the next-generation Internet after the web and the mobile network revolutions, in which humans (acting as digital avatars) can interact with other people and software applications in a three-dimensional (3D) virtual world. In this presentation, we first briefly introduce major concepts of Metaverse and the virtual service management. Then, we discuss applications of game theory in the virtual service management.

Jun 26 - Jul 2, 2022