The mini-course is an introduction to the analysis of infinity−harmonic functions, a subject that grew mature in recent years in the field of nonlinear partial differential equations. The material covered ranges from the Lipschitz extension problem to questions of existence, uniqueness and regularity for infinity−harmonic functions. A rigorous and detailed analysis of the equivalence between being absolutely minimising Lipschitz, enjoying comparison with cones and solving the infinity–Laplace equation in the viscosity sense is the backbone of the course. A few regularity results (including the Harnack inequality and the local Lipschitz continuity) and an easy proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen complete the course.

The mini-course is an introduction to the analysis of infinity−harmonic functions, a subject that grew mature in recent years in the field of nonlinear partial differential equations. The material covered ranges from the Lipschitz extension problem to questions of existence, uniqueness and regularity for infinity−harmonic functions. A rigorous and detailed analysis of the equivalence between being absolutely minimising Lipschitz, enjoying comparison with cones and solving the infinity–Laplace equation in the viscosity sense is the backbone of the course. A few regularity results (including the Harnack inequality and the local Lipschitz continuity) and an easy proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen complete the course.

The mini-course is an introduction to the analysis of infinity−harmonic functions, a subject that grew mature in recent years in the field of nonlinear partial differential equations. The material covered ranges from the Lipschitz extension problem to questions of existence, uniqueness and regularity for infinity−harmonic functions. A rigorous and detailed analysis of the equivalence between being absolutely minimising Lipschitz, enjoying comparison with cones and solving the infinity–Laplace equation in the viscosity sense is the backbone of the course. A few regularity results (including the Harnack inequality and the local Lipschitz continuity) and an easy proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen complete the course.

The mini-course is an introduction to the analysis of infinity−harmonic functions, a subject that grew mature in recent years in the field of nonlinear partial differential equations. The material covered ranges from the Lipschitz extension problem to questions of existence, uniqueness and regularity for infinity−harmonic functions. A rigorous and detailed analysis of the equivalence between being absolutely minimising Lipschitz, enjoying comparison with cones and solving the infinity–Laplace equation in the viscosity sense is the backbone of the course. A few regularity results (including the Harnack inequality and the local Lipschitz continuity) and an easy proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen complete the course.

The aim of this conference is to bring together researchers and practitioners in the interdisciplinary field of biodevices, which spans across electronics, medicine, engineering, material sciences, and related areas.  The conference is a continuation of a series that started this year with the KAUST Research Conference on New Trends in Biosensors and Bioelectronics.

Abstract

The goal of computer vision is to build “intelligent” machines

Abstract

The 2017 Lancet Commission on Pollution and Health estimated that air pollution was respo

In this talk, we represent recent advances of radio frequency (RF) sensing technology for healthcare, specifically in monitoring human activities inside homes, retirement facilities, and hospitals. Sensing technologies and data analytics are considered powerful tools in efficient indoor monitoring of human activities.  Monitoring of activities of daily living (ADL) can identify falls, which are considered as the leading cause of fatal and non-fatal injuries for people aged 65 and over. It can also detect variants in activity patterns and changes in routines and lifestyle as well as the state of physical, cognitive, and psychological health of the person. In addition to monitoring ADL, RF-based gesture recognition using hands and arms is shown to be an important contactless technology for Man-Machine-Interface (MMI). Adding to the indoor applications, RF-based vital sign monitoring has vast medical use, as respiration and heartbeats are essential diagnostic barometers for many health problems. More recently, RF sensors have also been proposed for gait analysis for rehabilitation and timely diagnosis of many neurological, orthopedic and medical conditions. Changes in gait patterns can also be precursors of falls. In this talk, we present successful examples in each of the above application areas and discuss pertinent open problems worthy of investigations.

Abstract

The crucial feature of neuronal ensembles i

As autonomy in individual robots becomes advanced, one of the next challenges is to coordinate multiple of such intelligent robots, which are then expected to innovatively transform legacy industries (e.g., warehouse automation, connected-vehicle management, etc.). Towards collaboration of multiple robots, this talk will particularly introduce a game-theoretical framework for clustering a large number of multiple robots and assigning the robot teams to given tasks, where the network of the robots is strongly connected and the individuals are asynchronous. The proposed decentralised algorithm guarantees convergence of selfish agents having social inhibition towards a Nash stable partition (i.e., social agreement) within polynomial time.

Approximating the solution to an evolutionary partial differential equation by a set of "moving particles" has several advantages. It validates the use of a continuity equation in an "individuals-based" modeling setting, it provides a link between Lagrangian and Eulerian description, and it defines a "natural" numerical approach to those equations. I will describe recent rigorous results in that context. The main one deals with one-dimensional scalar conservation laws with nonnegative initial data, for which we prove that the a suitably designed "follow-the-leader" particle scheme approximates entropy solutions in the sense of Kruzkov in the many particle limit. Said result represents a new way to solve scalar conservation laws with bounded and integrable initial data. The same method applies to second order traffic flow models, to nonlocal transport equations, and to the Hughes model for pedestrian movements.

Election hacking, power grid cyber-attacks, troll farms, fake news, ransomware, and other terms have entered our daily vocabularies and are here to stay. Cybersecurity touches nearly every part of our daily lives. Most importantly, national security and economic vitality rely on a safe, resilient, and stable cyber-space. We rely on cyber-physical systems with hardware devices, software platforms, and network systems to connect, travel, communicate, power our homes, provide health care, run our economy, etc. However, cyber-threats and attacks have grown exponentially over the past years, exposing both corporate and personal data, disrupting critical operations, causing a public health and safety impact, and imposing high costs on the economy. In this talk, we will focus on cyber-physical energy systems (CPES) as the backbone of critical infrastructure, and provide a research perspective and present red team security threats, challenges, and blue team countermeasures. We will discuss recent approaches on developing low-budget targeted cyberattacks against CPES, designing resilient methods against false data, and the need for an accurate assessment environment achieved through the inclusion of hardware-in-the-loop testbeds.

In this seminar, I will present our work on manipulating magnetization with acoustic waves. The temporally and spatially varying strain in acoustic waves produces a corresponding change in the local anisotropy of magnetostrictive materials through the Villari effect. This magneto-acoustic coupling may be used for patterning magnetic films and for nonlinear signal processing such as amplification and correlation of spin waves. I will discuss our experiments and results towards these application possibilities, and also present the techniques we have developed to characterize magnetostriction. 

In this talk I will discuss statistical models which incorporate temperature response to the radiative forcing components. The models can be used to estimate important climate sensitivity measures and give temperature forecasts. Bayesian inference is obtained using the methodology of integrated nested Laplace approximation and Monte Carlo simulations. The resulting approach will be demonstrated in analyzing instrumental data and Earth system model ensembles.

In the history of humankind, domestication was invented as anthropogenic evolution that fulfills mankind’s critical food demand. The domestication is simply based on mating processes and subsequent selection processes to pick up better hybrid offspring that have advantageous combinations of genomes. Taking advantage of machine learning classifier, we discovered a number of sub-genomic regions that have been incorporated in the rice genomes through production of hybrid offspring during domestication. This so-called “introgression” event is disclosed as an essential key of domestication process. This eventually leads to construction of the AI-aided Smart Breeding Platform to accumulate all the breeding histories of crop species into an Integrated Breeding Knowledgebase.

Abstract

Current genetic diagnosis by next-g

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.

Graduate Seminar Part 2. Fiber-optic distributed acoustic sensor (DAS) and distributed temperature sensor (DTS) are considered important for many applications. It is challenging to design a hybrid DAS-DTS system using the same optical fiber because the operation principles of the two sensors are different. In this talk, we summarize the concept of using the widespread standard multimode fiber (MMF) for simultaneous distributed acoustic and temperature sensing. In particular, we operate the MMF in a quasi-single-mode (QSM) state to simultaneously fulfill the functional requirements of the DAS and DTS. This technique is significant for many industrial applications because it efficiently tackles a long-standing issue in practical implementation. 

Graduate Seminar Part 1. In this talk, catalyst- and mask-free GaN nanowires ensemble were grown by plasma-assisted molecular beam epitaxy (PA-MBE) under nitrogen-rich condition. Prior to optoelectronic device realization, we conducted fundamental studies including diffusion-induced growth mechanisms on various substrates. On bare fused silica substrate, without any buffer layer, hundreds-of-nanometer scale grains of GaN nanowires were examined by SEM and interfaces were investigated by TEM. Despite the poly-crystalline properties of the coalescent columnar GaN layer, each grain showed the preferential orientation along the c-axis growth direction. To provide conductivity and transparency on amorphous fused silica as a thermally durable substrate, transparent conductive oxide (TCO) layers were deposited by RF magnetron sputtering method on a fused silica glass substrate. Next, for the heterogeneous integration toward solar cell application, we introduced n-GaN nanowires as an electron transport layer (ETL) for methylammonium lead iodide (MAPbI3) perovskite solar cells (PSCs). n-GaN nanowires showed high electron mobility and UV blocking characteristics with MAPbI3. Moreover, finite-difference time-domain (FDTD) simulation confirmed that the roughened interfaces of GaN nanowire arrays are helpful for photon recycling. These achievements can open a new pathway for the heterogeneous integration of group-III nitride and perovskite semiconductors and substrate-independent epitaxy.

Secondary quantities such as energy and entropy can be very important for numerical methods. Firstly, preserving these quantities can ensure that non-physical behavior is excluded. Secondly, preserving such quantities can result in stability estimates. Finally, preserving the correct energy/entropy evolution in time can result in additional desirable properties such as lower numerical errors. In this talk, a brief overview of some recent advances concerning energy and entropy preserving numerical methods for ordinary and partial differential equations will be given, together with an outlook on future research directions and applications.

Abstract

The demand for increasingly multidisciplinary reliable simulations, for both analysis and

The amount of collected medical data and computational power are growing rapidly, which creates new opportunities to impact and improve healthcare by advanced analytics and data science. We aim to bring together practitioners and researchers from across the Kingdom to exchange knowledge and explore possible collaborations. To register, please, fill form here.

Robotics is set to play an ever increasingly important role in society, due to its influence in every aspect of life, including medicine and healthcare, manufacturing, services..etc

In this talk we consider the Cauchy problem for the 2D Euler equations for incompressible inviscid fluids. It is well-known that given a smooth initial datum, the Cauchy problem is  well-posed and in particular the energy is conserved and the vorticity is transported by the flow of the velocity. When we consider weak solutions this might not be the case anymore. We will review some recent results obtained in collaboration with Gianluca Crippa and Gennaro Ciampa where we extend those properties to the case of irregular vorticities. In particular, under low integrability assumptions on the vorticity we show that certain approximations important from a physical and a numerical point of view converge to solutions satisfying those properties.

In Visualization, the success or failure of an analysis often depends on the choice of some subtle parameters or design choices. While simple heuristics are often sufficient, in some cases they make the analysis miserably fail. We present three approaches in visualization where a careful choice of optimal parameters results in completely new algorithms: 1) the choice of a reference frame for finding objective vortices in flow visualization, 2) the choice of a scaling of high-dimensional data sets for finding linear projections to 2D in information visualization, and 3) the choice of a feature definition along with numerical extraction methods for visualizing recirculation phenomena in flows.