Marco Cirant, Assistant Professor, Mathematic Department, University of Padova, Italy
Thursday, June 10, 2021, 14:00
- 17:00
https://kaust.zoom.us/j/97279416022
Contact Person
In this short course I will introduce some elements of bifurcation theory, such as the Lyapunov-Schmidt reduction, the bifurcation from the simple eigenvalue, and the Krasnoselski bifurcation theorem. Then, I will discuss some applications to the theory of MFG systems: existence of periodic in time solutions, and multi-population problems.
Marco Cirant, Assistant Professor, Mathematic Department, University of Padova, Italy
Tuesday, June 08, 2021, 14:00
- 17:00
https://kaust.zoom.us/j/94665268072
Contact Person
In this short course I will introduce some elements of bifurcation theory, such as the Lyapunov-Schmidt reduction, the bifurcation from the simple eigenvalue, and the Krasnoselski bifurcation theorem. Then, I will discuss some applications to the theory of MFG systems: existence of periodic in time solutions, and multi-population problems.
Tuesday, June 01, 2021, 16:00
- 18:00
https://kaust.zoom.us/j/96960741449
Contact Person
Due essentially to the difficulties associated with obtaining explicit forms of stationary marginal distributions of non-linear stationary processes, appropriate characterizations of such processes are worked upon little. After discussing an elaborate motivation behind this thesis and presenting preliminaries in Chapter 1, we characterize, in Chapter 2, the stationary marginal distributions of certain non-linear multivariate stationary processes. To do so, we show that the stationary marginal distributions of these processes belong to specific skew-distribution families, and for a given skew-distribution from the corresponding family, a process, with stationary marginal distribution identical to that given skew-distribution, can be found.
Wednesday, May 26, 2021, 18:00
- 19:30
https://kaust.zoom.us/j/93887554721
Contact Person
Wavefront sensing is a fundamental problem in applied optics. Wavefront sensors that work in a deterministic manner are of particular interest. Initialized with a unified theory for classical wavefront sensors, this dissertation discusses relevant properties of wavefront sensor designs. Based on which, a new wavefront sensor, termed Coded Wavefront Sensor, is proposed to leverage the advantages of the analysis, especially the lateral wavefront resolution. A prototype was built to demonstrate this new wavefront sensor.
Wilfrid Gangbo, Professor of mathematics at the University of California, Los Angeles
Tuesday, May 25, 2021, 19:00
- 21:00
https://kaust.zoom.us/j/95232883217
Contact Person
We recall the state of the art and the role of polyconvexity in the calculus of variations. Then we keep our focus on a particular polyconvex function, applicable to the study of Euler incompressible fluids. We prove the existence, uniqueness, and regularity of minimizers of a polyconvex functional which corresponds to the H1-projection of measure-preserving maps. Our result introduces a new criteria on the uniqueness of the minimizer, based on the smallness of the Lagrange multiplier. No estimate on the second derivatives of the pressure is needed to get a unique global minimizer. We introduce a minimizing movement scheme to construct Lr-solutions of the Navier-Stokes equation (NSE) for a short time interval. Our scheme is an improved version of the split scheme introduced in Ebin–Marsden in 1970, and allows us to solve the equation with less regular initial data as opposed to more regular initial data requirement in the 1970 Ebin–Marsden’s work. (Most of the material of these lectures is based on a joint work with M. Jacobs and I. Kim).
H. Vincent Poor, Michael Henry Strater University Professor, Princeton University
Tuesday, May 25, 2021, 15:30
- 16:30
https://kaust.zoom.us/j/98847418788
Contact Person
Fifth generation (5G) wireless communication networks are being deployed worldwide and more capabilities are in the process of being standardized, such as massive connectivity, ultra-reliability, and low latency. However, 5G will not meet all requirements of the future, and sixth generation (6G) wireless networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, greater intelligence and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architectures, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. One vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication networks. Multiple spectra will be exploited to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the very large datasets generated by heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of AI-related technologies. And, fourth, network security will have to be strengthened when developing 6G networks. This talk will review recent advances and future trends in these four aspects.
Wilfrid Gangbo, Professor of mathematics at the University of California, Los Angeles
Tuesday, May 11, 2021, 19:00
- 21:00
https://kaust.zoom.us/j/94916518261
Contact Person
We recall the state of the art and the role of polyconvexity in the calculus of variations. Then we keep our focus on a particular polyconvex function, applicable to the study of Euler incompressible fluids. We prove the existence, uniqueness, and regularity of minimizers of a polyconvex functional which corresponds to the H1-projection of measure-preserving maps. Our result introduces a new criteria on the uniqueness of the minimizer, based on the smallness of the Lagrange multiplier. No estimate on the second derivatives of the pressure is needed to get a unique global minimizer. We introduce a minimizing movement scheme to construct Lr-solutions of the Navier-Stokes equation (NSE) for a short time interval. Our scheme is an improved version of the split scheme introduced in Ebin–Marsden in 1970, and allows us to solve the equation with less regular initial data as opposed to more regular initial data requirement in the 1970 Ebin–Marsden’s work. (Most of the material of these lectures is based on a joint work with M. Jacobs and I. Kim).
Thursday, May 06, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/94262797011?pwd=ZXBBcnltQ3JvZkdhWFZjTEptL3FmUT09
Contact Person

Abstract

As simulation and analytics enter the exascale era, numerical algorithms must span a wide

Wilfrid Gangbo, Professor of mathematics at the University of California, Los Angeles
Tuesday, May 04, 2021, 19:00
- 21:00
https://kaust.zoom.us/j/96125002593
Contact Person
We recall the state of the art and the role of polyconvexity in the calculus of variations. Then we keep our focus on a particular polyconvex function, applicable to the study of Euler incompressible fluids. We prove the existence, uniqueness, and regularity of minimizers of a polyconvex functional which corresponds to the H1-projection of measure-preserving maps. Our result introduces a new criteria on the uniqueness of the minimizer, based on the smallness of the Lagrange multiplier. No estimate on the second derivatives of the pressure is needed to get a unique global minimizer. We introduce a minimizing movement scheme to construct Lr-solutions of the Navier-Stokes equation (NSE) for a short time interval. Our scheme is an improved version of the split scheme introduced in Ebin–Marsden in 1970, and allows us to solve the equation with less regular initial data as opposed to more regular initial data requirement in the 1970 Ebin–Marsden’s work. (Most of the material of these lectures is based on a joint work with M. Jacobs and I. Kim)
Lenore J. Cowen is a Professor in the Computer Science Department at Tufts University
Monday, May 03, 2021, 18:30
- 19:30
https://kaust.zoom.us/j/98889531668
Contact Person
The 2016 DREAM Disease Module Identification Challenge was developed to systematically assess the state of computational module identification methods on a diverse collection of molecular networks. Six different anonymized networks were presented with the gene names anonymized. The goal was to partition the genes into non-overlapping modules of from 3-100 genes each, based soley on the patterns of network connectivity.
Sunday, May 02, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/97706323720
Contact Person
Electromechanical switches were the core elements of the very first digital computers in early 20th century. While these switches were later replaced by the smaller, faster and more reliable "transistor" technology, they found a new life following the development of nanofabrication tools and Micro-electromechannical Systems (MEMS). In this seminar we will explore the most recent advances in the field of MEMS-based digital circuit and sensor design. We also examine the application of MEMS switches and resonators in building the most important blocks of a digital system, namely adders, multipliers, data converters, sequential and combinational complex logic, and discuss the future of this technology in the beyond-CMOS era.
Sunday, May 02, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/97706323720
Contact Person
We live in the age of information where electronics play a critical role in our daily life. Moore’s Law: performance over cost has inspired innovation in complementary metal oxide semiconductor (CMOS) technology and enabled high performance, ultra-scaled CMOS electronics. Moving forward as Internet of Everything (IoE) with advanced energy harvesting technologies seamlessly connects people, process, device and data – can CMOS technology be expanded further to achieve new features in CMOS electronics while maintaining and/or strengthening existing attributes? Can the existing applications be further strengthened and/or diversified? What potential applications may emerge? What energy harvesting technology will be able to meet the power requirements? My research addresses these questions through three main projects: 1) Nano-islands growth using an atomic layer deposition tool for application in low power non-volatile memory devices, 2) Multi-dimensional integration of heterogeneous materials and devices into a standalone system with a reduced area, high yield and low cost for IoT applications and 3) Flexing and stretching of inorganic solar cells with high efficiency for application in wearables, foldable electronics and solar drones. Finally, I propose a future direction for my research where I intend to leverage the materials growth, device fabrication and integration skills in order to contribute to a world where more connectivity and more computations are possible at a reduced energy consumption. This will be addressed using an innovative, smart and multifunctional memory device (MEMSOR) which enables In-Memory Sensing.
Georgiy L. Stenchikov, Professor, Earth Science and Engineering
Thursday, April 29, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/94262797011?pwd=ZXBBcnltQ3JvZkdhWFZjTEptL3FmUT09
Contact Person
Explosive volcanic eruptions are magnificent events that in many ways affect the Earth’s natural processes and climate. They cause sporadic perturbations of the planet’s energy balance, activating complex climate feedbacks and providing unique opportunities to better quantify those processes. We know that explosive eruptions cause cooling in the atmosphere for a few years, but we have just recently realized that they affect the major climate variability modes and volcanic signals can be seen in the subsurface ocean for decades. The volcanic forcing of the previous two centuries offsets the ocean heat uptake and diminishes global warming by about 30%. In the future, explosive volcanism could slightly delay the pace of global warming and has to be accounted for in long-term climate predictions. The recent interest in dynamic, microphysical, chemical and climate impacts of volcanic eruptions is also excited by the fact these impacts provide a natural analog for climate geoengineering schemes involving the deliberate development of an artificial aerosol layer in the lower stratosphere to counteract global warming. In this talk, I will discuss these recently discovered volcanic effects and specifically pay attention to how we can learn about the hidden Earth-system mechanisms activated by explosive volcanic eruptions.
Artificial Intelligence Initiative at KAUST
Wednesday, April 28, 2021, 08:30
- 16:30
https://kaust.zoom.us/j/96464686903
Contact Person

The Artificial Intelligence Initiative (AII) at KAUST cordially invites you to attend the KAUST Conference on Artificial Intelligence to be held on April 28-29, 2021. The conference is a two full-day event and will feature the broad AI landscape at KAUST by delving into topics on machine learning, AI theory and foundations, systems, and the many applications of AI in various scientific fields ranging from healthcare and biology to automation and visual computing.

The conference will be a hybrid event with both online streaming (Zoom Webinar) and limited in-person (Auditorium of Building 20) attendance.

Registration for the event is required for both in-person and online participation: Register here.

Registration for participants will remain open until midnight of April 25, 2021.

Prof. Peter Diggle, Statistics in the faculty of Health and Medicine, Lancaster University
Tuesday, April 27, 2021, 15:00
- 16:30
https://kaust.zoom.us/j/97813381559
Contact Person

In low-resource settings, disease registries do not exist, and prevalence mapping relies on data collected form surveys of disease prevalence taken in a sample of the communities at risk within the region of interest, possibly supplemented by remotely sensed images that can act as proxies for environmental risk factors. A standard geostatistical model for data of this kind is a generalized linear mixed model, Yᵢ ~ Binomial(mᵢ; P(xᵢ)) log [P(x)/{(1- P(xᵢ)}] = d(x)β + S(x), where Yᵢ is the number of positives in a sample of mi individuals at location xᵢ, d(x) is a vector of spatially referenced explanatory variables available at any location x within the region of interest, and S(x) is a Gaussian process.

In this talk, I will first review statistical methods and software associated with this standard model, then consider several methodological extensions and their applications to some Africa-wide control programmes for Neglected Tropical Diseases to demonstrate the very substantial gains in efficiency that can be obtained by comparison with currently used methods.

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain
Tuesday, April 27, 2021, 14:00
- 15:30
https://kaust.zoom.us/j/95514561794
Contact Person
There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain
Tuesday, April 27, 2021, 10:30
- 12:00
https://kaust.zoom.us/j/95514561794
Contact Person
There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
Muhammad Shafique , Professor, Division of Engineering, New York University Abu Dhabi (NYU-AD), United Arab Emirates
Monday, April 26, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/98889531668
Contact Person
Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world under unpredictable, harsh, and energy-/power-constrained scenarios. Therefore, such systems need to support not only the high-performance capabilities under tight power/energy envelop, but also need to be intelligent/cognitive and robust. This has given rise to a new age of Machine Learning (and, in general Artificial Intelligence) at different levels of the computing stack, ranging from Edge and Fog to the Cloud. In particular, Deep Neural Networks (DNNs) have shown tremendous improvement over the past years to achieve a significantly high accuracy for a certain set of tasks, like image classification, object detection, natural language processing, and medical data analytics. However, these DNN require highly complex computations, incurring huge processing, memory, and energy costs. To some extent, Moore’s Law help by packing more transistors in the chip.
Sunday, April 25, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/97706323720
Contact Person
We review our recent results on artificial-intelligent designed ultra-flat materials that embeds "physical" neural networks for different application in biomedical imaging, optics, displays, and structural color generation.
Prof. Mohamed Djemai, University Polytechnique Hauts-de-France
Thursday, April 22, 2021, 14:00
- 15:30
https://kaust.zoom.us/j/93170708922
Contact Person
This research is motivated not only because the control of some systems is implemented through the combination of continuous control laws with discrete switching logic but also because a wide range of physical and engineering systems exhibit hybrid behavior. Among the problems to be addressed, those of stabilization and observation are particularly important in order to always improve the efficiency of systems in terms of performance, lifetime and efficiency.
Thursday, April 22, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/94262797011?pwd=ZXBBcnltQ3JvZkdhWFZjTEptL3FmUT09
Contact Person
We develop several new communication-efficient second-order methods for distributed optimization. Our first method, NEWTON-STAR, is a variant of Newton's method from which it inherits its fast local quadratic rate. However, unlike Newton's method, NEWTON-STAR enjoys the same per iteration communication cost as gradient descent. While this method is impractical as it relies on the use of certain unknown parameters characterizing the Hessian of the objective function at the optimum, it serves as the starting point which enables us to design practical variants thereof with strong theoretical guarantees. In particular, we design a stochastic sparsification strategy for learning the unknown parameters in an iterative fashion in a communication efficient manner. Applying this strategy to NEWTON-STAR leads to our next method, NEWTON-LEARN, for which we prove local linear and superlinear rates independent of the condition number. When applicable, this method can have dramatically superior convergence behavior when compared to state-of-the-art methods. Finally, we develop a globalization strategy using cubic regularization which leads to our next method, CUBIC-NEWTON-LEARN, for which we prove global sublinear and linear convergence rates, and a fast superlinear rate. Our results are supported with experimental results on real datasets, and show several orders of magnitude improvement on baseline and state-of-the-art methods in terms of communication complexity.
Prof. Mohamed Djemai, University Polytechnique Hauts-de-France
Thursday, April 22, 2021, 10:30
- 12:00
https://kaust.zoom.us/j/91896126280
Contact Person
In recent years, new theoretical tools have been developed to describe complex systems more precisely, such as hybrid dynamical systems (HDS). Many works ranging from modelling to stabilisation, or control and observation have focused on the study of this class of systems. This research is motivated not only because the control of some systems is implemented through the combination of continuous control laws with discrete switching logic but also because a wide range of physical and engineering systems exhibit hybrid behavior. Among the problems to be addressed, those of stabilization and observation are particularly important in order to always improve the efficiency of systems in terms of performance, lifetime and efficiency.
Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain
Tuesday, April 20, 2021, 14:00
- 15:30
https://kaust.zoom.us/j/95514561794
Contact Person
There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain
Tuesday, April 20, 2021, 10:30
- 12:00
https://kaust.zoom.us/j/95514561794
Contact Person
The objective of this course is to give an introduction and cover recent aspects of dynamical modeling, monitoring and control of wastewater treatment processes. There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
Belen Masia, Associate Professor in the Computer Science Department at Universidad de Zaragoza
Monday, April 19, 2021, 12:00
- 13:00
https://kaust.zoom.us/j/98889531668
Contact Person
Virtual Reality (VR) can dramatically change the way we create and consume content in areas of our everyday life, including entertainment, training, design, communication or advertising. Understanding how people explore immersive virtual environments is crucial for many applications in VR, such as designing content, developing new compression algorithms, or improving the interaction with virtual humans. In this talk, we will focus on how to capture and model visual behavior of users in virtual environments.