Events

Feb 14 - Feb 20, 2021

• 

  Nanovisualization: Depicting the Tiny World Around Us

  Ivan Viola, Associate Professor, Computer Science

  Feb 17, 11:30 - 13:00

  KAUST

  nanovisualization

  Life at micron-scale is inaccessible to the naked eye. To aid the comprehension of nano- and micro-scale structural complexity, we utilize 3D visualization. Thanks to efficient GPU-accelerated algorithms, we witness a dramatic boost in the sheer size of structures that can be visually explored. As of today an atomistic model of the entire bacterial cell can be displayed interactively. On top of that, advanced 3D visualizations efficiently convey the multi-scale hierarchical architecture and cope with the high degree of structural occlusion which comes with dense packing of biological building blocks. To further scale up the size of life forms that can be visually explored, the rendering pipeline needs to integrate runtime construction of the biological structure. Assembly rules define how a body of a certain biological entity is composed. Such rules need to be applied on-the-fly, depending on where the viewer is currently located in the 3D scene to generate full structural detail for that part of the scene. We will review how to construct membrane-like structures, soluble protein distributions, and fiber strands through parallel algorithms, resulting in a collision-free biologically-valid scene. Assembly rules that define how a life form is structurally built need to be expressed in an intuitive way for the domain scientist, possibly directly in the three-dimensional space. Instead of placing one biological element next to another one for the entire biological structure by the modelers themselves, only assembly rules need to be specified and the algorithm will complete the application of those rules to form the entire biological entity. These rules are derived from current scientific knowledge and from all available experimental observations. The Cryo-EM Tomography is on rising and shows that we can already now reach the near-atomistic detail when employing smart algorithms. Our assembly rules extraction, therefore, needs to integrate with microscopic observations, to create an atomistic representation of specific, observed life forms, instead of generic models thereof. Such models then can be used in whole-cell simulations, and in the context of automated science dissemination.
• 

  Recent developments for stochastic processes and their applications

  Ahmed Kebaier, Associate Professor, Laboratory Analysis, Geometry and Application (LAGA), University Sorbonne Paris Nord (USPN)

  Feb 16, 12:00 - 13:00

  KAUST

  stochastic

  In this talk, we present our theoretical results recently developed around various types of applications. These results cover asymptotic and non-asymptotic analysis, functional limit theorems, concentration inequalities, and Malliavin calculus techniques elaborated for several classes of stochastic processes. We showcase through concrete examples the role of these results in taking up various challenges at the cutting-edge of modern applied probability.
• 

  High-dimensional inference for max-stable processes

  Dr. Boris Beranger, Lecturer in Statistics, University of New South Wales, Sydney

  Feb 16, 11:00 - 12:00

  KAUST

  extreme environmental events Max-stable processes

  Droughts, high temperatures and strong winds are key causes of the recent bushfires that have touched a major part of the Australian territory. Such extreme events seem to appear with increasing frequency, creating an urgent need to better understand the behavior of extreme environmental phenomena.
• 

  Existence theory for non-separable mean field games - Session 3

  David Ambrose, Professor, Department of Mathematics at Drexel University, USA

  Feb 15, 17:00 - 19:00

  KAUST

  The time-dependent PDE system for mean field games is a coupled pair of parabolic equations, one forward in time and the other backward in time. The lecturer will demonstrate two techniques for proving existence and uniqueness of solutions for this system. The first of these techniques is inspired by work in fluid dynamics, as a similar forward-backward structure for vortex sheets was discovered by Duchon and Robert in the 1980s. Adapting the ideas of Duchon and Robert gives existence and uniqueness of solutions for the time-dependent mean field games system in function spaces based on the Wiener algebra. The second technique to be demonstrated by the speaker uses Sobolev spaces, and is an adaptation of the energy method to the forward-backward setting.
• 

  Resilience is the Cybersecurity of the XXI century, and here's why! - 2021-02-15

  Feb 15, 12:00 - 13:00

  KAUST

  In a nutshell, Resilient Computing is a new paradigm based on modelling, architecting and designing computer systems so that: they have built-in baseline defences; such defences cope with virtually any quality of threat, be it accidental faults, design errors, cyber-attacks, or unexpected operating conditions; provide incremental protection of, and automatically adapt to, a dynamic range of threat severity; provide sustainable operation.

Feb 7 - Feb 13, 2021

• 

  Visible Light Communications Technology and Machine Learning - 2021-02-12

  Dr. Paul Anthony Haigh, Newcastle University, United Kingdom and Dr. Bo Tan, Tampere University, Finland

  Feb 12, 16:00 - 17:15

  KAUST

  vlc

  In this webinar we will give an overview of several key technologies related to our special issues in Frontiers of Communications and Networks; (1) visible light communications (VLC) and (2) applications of machine learning in optical and wireless communication systems.
• 

  Proper scoring rules and model selection for stochastic processes

  David Bolin, Associate Professor, Statistics

  Feb 11, 12:00 - 13:00

  KAUST

  In this talk, we begin by a brief introduction to proper scoring rules and their use in statistics. Then, we discuss an often overlooked problem: the up-weighting of observations with large uncertainty, which can lead to unintuitive rankings of models, by some of the most popular proper scoring rules, such as the continuously ranked probability score (CRPS), the MAE, and the MSE.
• 

  High Order Numerical Methods for Acoustic and Elastic Scattering

  Prof. Vianey Villamizar, Department of Mathematics, Brigham Young University, USA

  Feb 9, 14:00 - 15:00

  KAUST

  A focus of my current research is to develop numerical methods for the accurate simulation of sound and seismic waves. This waves usually occur in very large domains. For the computational purpose, the original unbounded wave problems need to be transformed into bounded ones. To accomplish this goal artificial boundaries are chosen to truncate the infinite domains. The challenge is to define absorbing boundary conditions (ABC) on these artificial boundaries such that the solutions of the new bounded problems approximate to a reasonable degree the solutions of the original unbounded problems in their common domains. In part, my efforts and those of my students and collaborators have been in deriving computational advantageous ABC and the formulation of a high order and high accurate numerical methods inside the truncated domain. In this talk, I will describe in some details our work. Also, I will include numerical results which demonstrate the improved accuracy and simplicity of our formulation when compared with commonly used ABC.
• 

  Existence theory for non-separable mean field games - Session 2

  David Ambrose, Professor, Department of Mathematics at Drexel University, USA

  Feb 8, 17:00 - 19:00

  KAUST

  The time-dependent PDE system for mean field games is a coupled pair of parabolic equations, one forward in time and the other backward in time. The lecturer will demonstrate two techniques for proving existence and uniqueness of solutions for this system. The first of these techniques is inspired by work in fluid dynamics, as a similar forward-backward structure for vortex sheets was discovered by Duchon and Robert in the 1980s. Adapting the ideas of Duchon and Robert gives existence and uniqueness of solutions for the time-dependent mean field games system in function spaces based on the Wiener algebra. The second technique to be demonstrated by the speaker uses Sobolev spaces, and is an adaptation of the energy method to the forward-backward setting.
• 

  Generative Adversarial Networks and Generative Modeling

  Peter Wonka, Professor, Computer Science

  Feb 8, 12:00 - 13:00

  KAUST

  I will review some background of generative adversarial modeling using GANs and discuss how our group has been using GANs for image editing.
• 

  Statistical models for studying biodiversity: challenges and contributions

  Antik Chakraborty, Postdoc, Department of Statistical Science, Duke University

  Feb 7, 16:00 - 17:00

  KAUST

  biodiversity

  A healthy ecosystem is essential to our well being and to ensure that we need a better understanding of the life or biodiversity around us. In the first part of this talk, I will introduce how modern technology is being used to collect data on biodiversity across space and time. These data come in complex forms such as DNA sequences, high-dimensional binary vectors, sound signals, etc. I will briefly touch upon the statistical challenges involved in making sense of these data. In the second part, I will elaborate on a project motivated by studying temporal patterns in bird vocalizations. I will introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed class of FRActional Probit (FRAP) models are based on the thresholding of a latent process consisting of an additive expansion of a smooth Gaussian process with a fractional Brownian motion. I will describe a Bayesian approach to inference using Markov chain Monte Carlo. Results from applying the model on Amazon bird vocalization data will be presented which provide substantial evidence for self-similarity and non-Markovian/Poisson dynamics. A hierarchical extension of the proposed model to accommodate vocalizations of multiple birds at the same time will also be discussed.
• 

  Leveraging Readily Available Data for Low Resource Natural Language Processing

  Derry Wijaya, Assistant Professor, Computer Science, Boston University

  Feb 7, 15:00 - 16:00

  KAUST

  Natural Language Processing

  State-of-the-art Natural Language Processing (NLP) systems nowadays are dominated by machine learning and deep learning models. However, most of these models often only work well when there are abundant labeled data for training. Furthermore, as these models typically have a large number of parameters, they require large compute resources to train. For the majority of languages in the world and the researchers working on these languages, however, abundant labeled data are a privilege and so do compute resources. How can we train generalizable NLP models that are effective even when labeled data are scarce and compute resources are limited? In this talk, I will present some of our solutions that leverage unsupervised or few-shot learning and readily available multilingual resources or multimodal data to improve machine translation and nuanced text classification such as news framing under these low resource settings.
• 

  Ariadne: Building safe autonomy with unproven algorithms

  Eric Feron, Professor, Electrical and Computer Engineering

  Feb 7, 12:00 - 13:00

  KAUST

  Ariadne safe autonomy unproven algorithms

  With the advent of increasingly intelligent algorithms, robots are capable of planning and performing increasingly challenging and creative tasks. Safety, however, remains an essential requirement on robotic behaviors. It is also a property that is hard or impossible to prove for virtually all intelligent algorithms of practical value. Ariadne is a model-based paradigm that enables the safe operation of many robotic systems, even though the algorithms involved with the operation may not be verifiable. Ariadne, or "plan B" engineering, will be illustrated in various current Robotics contexts derived from Ariadne's own Greek mythology, railroad systems, nuclear energy production, air transportation, and others.

Jan 31 - Feb 6, 2021

• 

  Effective Literature Search

  Nevena Tomic, Library Subject Specialist, PSE, KAUST

  Feb 4, 12:00 - 13:00

  KAUST

  This session will help you to improve the efficiency of your literature searches. You will learn basic search techniques – using Boolean operators, keyword search, concept search, truncation, etc. Two major interdisciplinary scientific databases – Web of Science and Scopus, as well as CEMSE specific resources in KAUST library collections will be presented.
• 

  Existence theory for non-separable mean field games - Session 1

  David Ambrose, Professor, Department of Mathematics at Drexel University, USA

  Feb 1, 17:00 - 19:00

  KAUST

  The time-dependent PDE system for mean field games is a coupled pair of parabolic equations, one forward in time and the other backward in time. The lecturer will demonstrate two techniques for proving existence and uniqueness of solutions for this system. The first of these techniques is inspired by work in fluid dynamics, as a similar forward-backward structure for vortex sheets was discovered by Duchon and Robert in the 1980s. Adapting the ideas of Duchon and Robert gives existence and uniqueness of solutions for the time-dependent mean field games system in function spaces based on the Wiener algebra. The second technique to be demonstrated by the speaker uses Sobolev spaces, and is an adaptation of the energy method to the forward-backward setting.
• 

  Enabling Accurate and Efficient Simulation in Visual Computing - Graduate Seminar - CS

  Dominik L. Michels, Associate Professor, Computer Science

  Feb 1, 12:00 - 13:00

  KAUST

  The overarching goal of Prof. Michels' Computational Sciences Group within KAUST's Visual Computing Center is enabling accurate and efficient simulations for applications in Scientific and Visual Computing.
• 

  Mechatronics: Synergy throughout Systems

  Shehab Ahmed, Professor, Electrical and Computer Engineering

  Jan 31, 12:00 - 13:00

  KAUST

  Mechatronics Synergy throughout Systems

  Actuators, electric vehicles, renewable energy systems, oil rigs and smart cities are all examples of complex systems that have evolved over time to better address societal needs. Mechatronics, the synergistic integration of electrical, mechanical and computing, has powered this evolution and enabled higher power density actuators, increased hosting of renewable energy in power grids, improved drilling efficiency and responsive cities. In this talk, I will share research highlights from the Mechatronics and Energy Systems Research Group (MERGE) to demonstrate value creation through engineered synergies.
• 

  Monte Carlo based Inference for State-space Models

  Sumeetpal Singh, Reader, Engineering Statistics, Department of Engineering, University of Cambridge

  Jan 31, 12:00 - 13:00

  KAUST

  Monte Carlo state-space models

  State-space models are widely used for the analysis of time-series data but full Bayesian inference is still elusive. I will review some applications of state-space models and recent endeavours towards efficient Monte Carlo sampling, in particular using Particle filtering and more recent Particle Markov Chain Monte Carlo methods. I will discuss the theoretical scalability of these methods with respect to the length of the observed time-series. Our theoretical results on their efficiency align well with many documented instances of their effectiveness based on extensive numerical studies. The talk will conclude with some open challenges to be pursued.

Jan 24 - Jan 30, 2021

• 

  Fractional calculus and partial differential equation - Session 2

  Fabio Camilli, Full Professor of Mathematical Analysis, Università di Roma, La Sapienza, Italy

  Jan 28, 15:00 - 18:00

  KAUST

  In this course, we provide a brief introduction to fractional calculus with a view to applying it to the study of time fractional partial differential equations. We will introduce the definitions and main properties of fractional integrals and derivatives, including those of Riemann-Liouville, Caputo and Grunwald-Letnikov. The previous results will serve as the main modeling tools for partial differential equations related to a class of non-Markovian stochastic processes, called subdiffusions. Then we will examine some results regarding time-fractional linear partial differential equations and conclude with a brief introduction to control problems and Mean Field Games for subdiffusion processes.
• 

  A personal and historical view of computational mathematics

  Tony Chan, President, King Abdullah University of Science and Technology

  Jan 28, 12:00 - 13:00

  KAUST

  Computational mathematics has a millennium long history but its modern incarnation started after the advent of electronic computers about 80 years ago. Scientifically, it lies in the intersection between mathematics, a subject with a long history, and computer sciences, a relatively new discipline. Its motivations, approaches and practitioners have derived from different fields, and it has also had to evolve and adapt to new tools and opportunities. My own scientific career overlaps quite a bit with the field’s modern evolution and in this talk, I’ll give a personal, as well as a “historical” view of the field.
• 

  Fractional calculus and partial differential equation - Session 1

  Fabio Camilli, Full Professor of Mathematical Analysis, Università di Roma, La Sapienza, Italy

  Jan 26, 15:00 - 18:00

  KAUST

  In this course, we provide a brief introduction to fractional calculus with a view to applying it to the study of time fractional partial differential equations. We will introduce the definitions and main properties of fractional integrals and derivatives, including those of Riemann-Liouville, Caputo and Grunwald-Letnikov. The previous results will serve as the main modeling tools for partial differential equations related to a class of non-Markovian stochastic processes, called subdiffusions. Then we will examine some results regarding time-fractional linear partial differential equations and conclude with a brief introduction to control problems and Mean Field Games for subdiffusion processes.
• 

  Building Better Datacenters - The Quest for Low Latency

  Simon Peter, Assistant professor, Computer Science, University of Texas, Austin

  Jan 25, 18:30 - 19:30

  KAUST

  In this talk, I focus on the adoption of low latency persistent memory modules (PMMs). PMMs upend the long-established model of remote storage for distributed file systems. Instead, by colocating computation with PMM storage we can provide applications with much higher IO performance, sub-second application failover, and strong consistency. To demonstrate this, I present Assise, a new distributed file system, based on a persistent, replicated coherence protocol that manages client-local PMM as a linearizable and crash-recoverable cache between applications and slower (and possibly remote) storage.
• 

  Biosensors challenges and opportunities

  Khaled Salama, Professor, Electrical and Computer Engineering

  Jan 24, 12:00 - 13:00

  KAUST

  Biosensors challenges opportunities

  No summary is available.
• 

  Building Latency-Critical Datacenter Systems

  Marios Kogias, Researcher, Computer Science, Microsoft Research, Cambridge

  Jan 24, 10:00 - 11:00

  KAUST

  In the first part of the talk, I will focus on ZygOS[SOSP 2017], a system optimized for μs-scale, in-memory computing on multicore servers. ZygOS implements a work-conserving scheduler within a specialized operating system designed for high request rates and a large number of network connections. ZygOS revealed the challenges associated with serving remote procedure calls (RPCs) on top of a byte-stream oriented protocol, such as TCP. In the second part of the talk, I will present R2P2[ATC 2019]. R2P2 is a transport protocol specifically designed for datacenter RPCs, that exposes the RPC abstraction to the endpoints and the network, making RPCs first-class datacenter citizens. R2P2 enables pushing functionality, such as scheduling, fault-tolerance, and tail-tolerance, inside the transport protocol, making it application-agnostic. I will show how using R2P2 allowed us to offload RPC scheduling to programmable switches that can schedule requests directly on individual cores.

Jan 17 - Jan 23, 2021

• 

  Elliptic PDEs: Regularity under minimal assumptions - Session 2

  Giuseppe Di Fazio,Professor of Mathematics at the University of Catania, Italy

  Jan 21, 10:00 - 13:00

  KAUST

  Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.
• 

  Elliptic PDEs: Regularity under minimal assumptions - Session 1

  Giuseppe Di Fazio, Professor of Mathematics at the University of Catania, Italy

  Jan 19, 10:00 - 13:00

  KAUST

  Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.
• 

  Building Scalable Network Stacks for Modern Applications

  Ahmed Saeed, Postdoctoral Associate, Computer Science, MIT

  Jan 17, 15:00 - 16:00

  KAUST

  This talk covers two research directions that address the shortcomings of existing network stacks. The first is on scalable software network stacks, solving problems in different components of operating systems and applications to allow a single server to handle data flows for tens of thousands of clients. The second is on Wide Area Network (WAN) congestion control, focusing on network-assisted congestion control schemes, where end-to-end solutions fail. The talk will conclude with a discussion of plans for future research in this area.

Jan 10 - Jan 16, 2021

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  Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning

  Arnulf Jentzen, Professor, Applied Mathematics Münster: Institute for Analysis and Numerics, University of Münster

  Jan 10, 14:00 - 15:00

  KAUST

  nonlinear Deep learning monte carlo algorithms

  In this talk we prove that suitable deep neural network approximations do indeed overcome the curse of dimensionality in the case of a general class of semilinear parabolic PDEs and we thereby prove, for the first time, that a general semilinear parabolic PDE can be solved approximatively without the curse of dimensionality.

Jan 3 - Jan 9, 2021

• 

  Mean Field Games: Numerical Methods and Applications

  Mathieu Laurière, Postdoc, Department of Operations Research and Financial Engineering, Princeton University

  Jan 5, 15:00 - 16:00

  KAUST

  mean-field games numerical methods

  In this talk, several numerical methods will be presented and illustrated on examples. Borrowing tools from stochastic analysis, optimization, partial differential equations and machine learning, these methods enable us to solve mean field games with possibly complex sources of noise or high dimensional state variables.

Dec 20 - Dec 26, 2020

• 

  What’s the Story with UAV Cellular Communications?

  Prof. Giovanni Geraci, Assistant Professor, University Pompeu Fabra (UPF) in Barcelona, Spain

  Dec 22, 16:00 - 17:15

  KAUST

  UV Communications

  What will it take for UAVs—and the associated ecosystem—to take off? Arguably, ubiquitous high-capacity links paired with hyper-reliable command and control all along. And indeed, meeting these aspirations may entail a full-blown mobile network support. While the understanding of UAV cellular communications has been advancing, many fundamental challenges remain to be addressed, with new applications demanding original solutions. In this talk, we blend academic and industrial views, navigating from 4G to 6G UAV use cases, requirements, and enabling technologies

Dec 13 - Dec 19, 2020

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  Wireless Communications using Light - not all wireless is at RF

  Prof. Steve Hranilovic, Associate Dean, McMaster University, Canada and Dr. Imran Shafique Ansari, Assistant Professor, University of Glasgow, United Kingdom

  Dec 15, 16:00 - 17:15

  KAUST

  FSO systems

  Due to the increasing scarcity of RF spectrum and growing interference due to multiple users, deploying next generation high-speed wireless networks is becoming increasingly difficult. The use of unlicensed optical bands for wireless communications has been heralded as an exciting development for future broadband access for indoor, underwater and space communication links.

Dec 6 - Dec 12, 2020

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  Geospatial Data Science for Public Health Surveillance - Graduate Seminar

  Dec 10, 12:00 - 13:00

  KAUST

  Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. In this talk, I will give an overview of my research which focuses on the development of geospatial methods and interactive visualization applications for health surveillance. I will present disease risk models where environmental, demographic and climatic data are used to predict the risk and identify targets for intervention of lymphatic filariasis in sub-Saharan Africa, and leptospirosis in a Brazilian urban slum. I will also show the R packages epiflows for risk assessment of travel-related spread of disease, and SpatialEpiApp for disease mapping and the detection of clusters. Finally, I will describe my future research and how it can inform better surveillance and improve population health globally.
• 

  Redesigning CMOS Electronics: What, Why and How?

  Dec 6, 12:00 - 13:00

  KAUST

  Redesigning CMOS electronics

  A little more than half of the world’s population enjoy benefits of information technology which is enabled by complementary metal oxide semiconductor (CMOS) electronics. Going forward, we will enjoy further augmentation of quality of life through integrated CMOS electronic systems consisting of logic, memory, communication devices, energy storage and harvester, power management units, sensors and actuators. Their main attributes will include but not limited to high performance and storage capacity for data management; seamless connectivity; energy efficiency; hyper-scale integration density; appropriate functionalities based on their applications and operational environment; reliability and safety; and finally affordability and simplicity to expand their user base to include those who do not have any access to them today. Even using last fifty years’ wealth of knowledge and experience, such integrated electronic system development and deployment is a monumental engineering challenge. From that perspective, redesigning CMOS electronics might seem to be an overly ambitious goal specially, if that means transformation of such physically rigid complex electronic systems into a fully flexible one. To address this intriguing challenge, we have developed a unique coin like architecture based soft singular platform, which can be used as the building block of standalone fully flexible CMOS electronic system with all the aforementioned characteristics. We have devised an effective heterogeneous integration strategy based on mature and reliable CMOS technology only to integrate hybrid materials and diverse set of devices for multi-disciplinary applications. These will be the focus of this talk.

Nov 29 - Dec 5, 2020

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  Mini Courses by Prof Piermarco Cannarsa - Session 2

  Professor Piermarco Cannarsa, Mathematical Analysis at the University of Rome Tor Vergata, Italy

  Dec 3, 15:00 - 18:00

  KAUST

  The theory of Mean Field Games (MFG) has been developed in the last two decades by economists, engineers, and mathematicians in order to study decision making in very large populations of “small" interacting agents. This short course will be focused on deterministic MFG, which are associated with a first order PDE system. We will address the problem assuming that agents are subject to state constraints, when classical PDE techniques are of little help. First, we will show how to prove the existence of solutions by the so-called Lagrangian approach, which interprets equilibria as certain measures on the space of paths that each agent can choose. Then, we will address regularity issues for such generalized solutions, deriving point-wise properties that allow to recover the typical MFG system. Finally, we will study the asymptotic behavior of solutions to the constrained MFG system as time goes to infinity, borrowing ideas from weak KAM theory.
• 

  Modelling and Simulation of Biological Systems - 2020-12-03

  Gabriel Wittum, Professor, Applied Mathematics and Computational Sciences

  Dec 3, 12:00 - 13:00

  KAUST

  Biological systems are distinguished by their enormous complexity and variability. That is why mathematical modeling and computational simulation of those systems is very difficult, in particular thinking of detailed models which are based on first principles. The difficulties start with geometric modeling which needs to extract basic structures from highly complex and variable phenotypes, on the other hand also has to take the statistic variability into account. Moreover, the models of the processes running on these geometries are not yet well established, since these are equally complex and often couple many scales in space and time. Thus, simulating such systems always means to put the whole frame to test, from modelling to the numerical methods and software tools used for simulation. These need to be advanced in connection with validating simulation results by comparing them to experiments.
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  Conquering the Terahertz Band: From Theory to Practice

  Prof. Josep M. Jornet, Northeastern University, in Boston, MA

  Dec 1, 15:45 - 17:15

  KAUST

  THz sensing THz signal source

  The need for higher data-rates and more ubiquitous connectivity for an ever-increasing number of wirelessly connected devices motivates the exploration of uncharted spectral bands. In this context, Terahertz (THz)-band (0.1–10 THz) communication is envisioned as a key wireless technology of the next decade. The very large bandwidth available at THz frequencies (tens to hundreds of consecutive GHz) can alleviate the spectrum scarcity problem while enabling wireless Terabit-per-second (Tb/s) links in personal and local area networks, backhaul for urban and rural areas, and even space networks.
• 

  Mean Field Games with State Constraints - Session 1

  Professor Piermarco Cannarsa, Mathematical Analysis at the University of Rome Tor Vergata, Italy

  Dec 1, 15:00 - 18:00

  KAUST

  The theory of Mean Field Games (MFG) has been developed in the last two decades by economists, engineers, and mathematicians in order to study decision making in very large populations of “small" interacting agents. This short course will be focused on deterministic MFG, which are associated with a first order PDE system. We will address the problem assuming that agents are subject to state constraints, when classical PDE techniques are of little help. First, we will show how to prove the existence of solutions by the so-called Lagrangian approach, which interprets equilibria as certain measures on the space of paths that each agent can choose. Then, we will address regularity issues for such generalized solutions, deriving point-wise properties that allow to recover the typical MFG system. Finally, we will study the asymptotic behavior of solutions to the constrained MFG system as time goes to infinity, borrowing ideas from weak KAM theory.
• 

  Transparent and Robust Causal Inference in Data Science

  Carlos Cinelli, Ph.D. candidate, Department of Statistics, UCLA

  Nov 30, 16:30 - 17:30

  KAUST

  statistical inference data science

  The past few decades have witnessed rapid and unprecedented theoretical progress in the science of causal inference, ranging from the “credibility revolution” with the popularization of quasi-experimental designs, to the development of a complete solution to non-parametric identification with causal graphical models. Most of these theoretical progress, however, relies on strong, exact assumptions, such as the absence of unobserved common causes, or the absence of certain direct effects. Unfortunately, more often than not these assumptions are very hard to defend in practice. This leads to two undesirable consequences for applied quantitative work in the data-intensive sciences: (i) important research questions may be neglected, simply because they do not exactly match the requirements of current methods; or, (ii) researchers may succumb to making the required “identification assumptions” simply to justify the use of available methods, but not because these assumptions are truly believed (or understood). In this talk, I will discuss new theories, methods, and software for permitting causal inferences under more flexible and realistic settings. These tools empower scientists, and policymakers to both examine the sensitivity of causal inferences to violations of its underlying assumptions, and also to draw robust and trustworthy conclusions from settings in which traditional methods fail.
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  Enabling Accurate and Efficient Simulation in Visual Computing - Public Colloquium

  Dominik L. Michels, Associate Professor, Computer Science

  Nov 30, 14:30 - 16:00

  KAUST

  visual computing

  The overarching goal of Prof. Michels' Computational Sciences Group within KAUST's Visual Computing Center is enabling accurate and efficient simulations for applications in Scientific and Visual Computing. Towards this goal, the group develops new principled computational methods based on solid theoretical foundations. This talk covers a selection of previous and current work presenting a broad spectrum of research highlights ranging from simulating stiff phenomena such as the dynamics of fibers and textiles, over liquids containing magnetic particles, to the development of complex ecosystems and weather phenomena. Moreover, connection points to the growing field of machine learning are addressed and an outlook is provided with respect to selected technology transfer activities.
• 

  Research at the Image and Video Understanding Lab (IVUL) - Graduate Seminar - CS

  Bernard Ghanem, Professor, Electrical and Computer Engineering

  Nov 30, 12:00 - 13:00

  KAUST

  In this talk, I will give an overview of research done in the Image and Video Understanding Lab (IVUL) at KAUST. At IVUL, we work on topics that are important to the computer vision (CV) and machine learning (ML) communities, with emphasis on three research themes: Theme 1 (Video Understanding), Theme 2 (Visual Computing for Automated Navigation), Theme 3 (Fundamentals/Foundations).
• 

  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 3

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 29, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
• 

  Mobile Microrobotics

  Hussein Hussein, Postdoctoral Research Fellow, Electrical and Computer Engineering

  Nov 29, 12:00 - 13:00

  KAUST

  mobile Microrobotics

  The implementation of robotic solutions to accomplish automated tasks in industrial sectors has tremendously increased the human performance capacity and enhanced the cost, quality and delivery time for different tasks and products. Having already proven their utility at the macroscale, robots also show their usefulness when we approach the infinitely small dimensions, for applications such as inspection, cell manipulation, assembly, biopsy and drug delivery. The way to the microworld is not that simple; reducing the size of robots from macro scale to micro scale cannot be accomplished by merely miniaturizing the different parts of an existing robot. The variation in the scale of physical effects with the size scale and the difficulties of fabrication and assembly at the micro scale make the macro-solutions for actuation and sensing unsuitable for microdevices. Other actuation mechanisms with deformable structures and integrated sensing solutions are more efficient at microscale and compatible with microfabrication limitations. This talk focuses on different aspects related to mobile microrobots, including limitations and challenges, actuation mechanisms, power delivery, and current works in our team for the development of mobile microrobots.

Nov 22 - Nov 28, 2020

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  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 2

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 26, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
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  The Tetracopter: A modular, self-similar flying robot

  Eric Feron, Professor, Electrical and Computer Engineering

  Nov 26, 12:00 - 13:00

  KAUST

  Modular robotics deals with robots that are an assemblage of smaller sized and often identical robots. The benefits of modular robots are many, chief among them being how easily they can be transported from one location to another. Moreover, their size can be adjusted according to the task at hand without requiring extensive redesign or specialization, therefore making them the object of significant research efforts.
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  Energy-Efficient Non-Orthogonal Multicast and Unicast Transmission of Cell-Free Massive MIMO Systems with SWIPT

  Prof. Minghua Xia, Sun Yat-sen University, China & Prof. Zilong Liu,University of Essex, United Kingdom

  Nov 24, 16:00 - 17:15

  KAUST

  SWIPT

  To suit massive connectivity of machine-type communications in smart cities, this talk discusses the energy-efficient resource allocation for layered-division multiplexing (LDM) based non-orthogonal multicast and unicast transmission in cell-free massive multiple-input multiple-output (MIMO) systems, where each user equipment (UE) performs wireless information and power transfer simultaneously. Non-orthogonal multiple access (NOMA) is an emerging paradigm for the enabling of massive connectivity in 5G networks and beyond.
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  Towards Accurate Biomedical Genomics Anywhere Anytime - Public Colloquium

  Xin Gao, Program Chair, Computer Science

  Nov 24, 14:00 - 15:30

  KAUST

  In this talk, I will first give an overview of the research activities in Structural and Functional Bioinformatics Group (http://sfb.kaust.edu.sa). I will then focus on our efforts on developing computational methods to tackle key open problems in Nanopore sequencing. In particular, I will introduce our recent works on developing a collection of computational methods to decode raw electrical current signal sequences into DNA sequences, to simulate raw signals of Nanopore, and to efficiently and accurately align electrical current signal sequences with DNA sequences. I will further introduce their applications in biomedicine and healthcare.
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  BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data

  Meini Tang, M.S. Student, Statistics

  Nov 24, 09:00 - 10:00

  KAUST

  Intrinsic connectivity networks (ICNs) refer to brain functional networks that are consistently found under various conditions, during tasks or at rest. Some studies demonstrated that while some stimuli do not impact intrinsic connectivity, other stimuli actually activate intrinsic connectivity through suppression, excitation, moderation or modification. Most analyses of fMRI data use ad-hoc methods to estimate the latent structure of ICNs. Modeling the effects on ICNs has also not been fully investigated. We propose a Bayesian Intrinsic Connectivity Network (BICNet) model, an extended Bayesian dynamic sparse latent factor model, to identify the ICNs and quantify task-related effects on the ICNs. BICNet has the following advantages: (1) It simultaneously identifies the individual and group-level ICNs; (2) It robustly identifies ICNs by jointly modeling rfMRI and tfMRI; (3) Compared to ICA-based methods, it can quantify the difference of ICN amplitudes across different states; (4) The sparsity of ICNs automatically performs feature selection, instead of ad-hoc thresholding. We apply BICNet to the rfMRI and language tfMRI data from the HCP and identify several ICNs related to distinct language processing functions.
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  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 1

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 23, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
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  From a Virtual Red Sea to the Urban Scales of NEOM: A Decade of Progress Driven by Computational Sciences

  Ibrahim Hoteit, Professor, Earth Science and Engineering

  Nov 23, 12:00 - 13:00

  KAUST

  The talk will present our decade-long efforts to build an integrated data-driven modeling system to study and predict the circulation and climate of the Arabian Peninsula at all scales. Starting from a general description of the Virtual Red Sea Initiative at its achievements so far, I will then outline our ongoing research under the KAUST Centre of Excellence for NEOM to develop new tools to seamlessly project and study the environment at the urban scales of NEOM. I will in particular discuss the involved scientific opportunities and challenges in terms of computational Sciences, including our extreme computational requirements, and the handling, analysis and visualization of very large datasets.
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  Efficient and Accurate Numerical Methods for Transient Electromagnetic Analysis - 2020

  Hakan Bagci, Associate Dean for Students, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 22, 12:00 - 13:00

  KAUST

  Efficient numerical Methods Transient electromagnetic

  Electromagnetic devices and systems are at the heart of technological advances revolutionizing many fields of science and engineering including energy management, biomedical electronics, communications and computing, and even environmental monitoring and civil design. Many of these systems are electrically large, their frequency of operation has a wide dynamic range, their device components are geometrically intricate with dimensions varying by orders of magnitude, and finally their optimal design requires many repetitions of characterizations with different parameters.